You’re passionate about big data. You’re ready to commit to an advanced degree. But should it be the MS or PhD? Our guide to doctoral programs in data science is here to help. It has advice on benefits & downsides, job opportunities, dissertation topics, courses, costs, and more. Just want the schools? Skip ahead to our complete list of data-related PhD programs.
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Why Earn a PhD in Data Science?
A PhD in Data Science is a research degree designed to give you a deep-rooted knowledge of statistics, programming, data analysis, and subjects relevant to your area of interest (e.g. machine learning, artificial intelligence, etc.).
The key word here is research:
- You’ll be expected to conduct your own experiments in a specific field.
- You’ll focus on theory—both pure and applied—to discover why certain methodologies are used.
- You’ll take apart tools & technologies to determine how they’re built.
Benefits vs. Downsides
The benefits and downsides of a PhD are always being debated, and Quora has plenty of insightful answers from data scientists on this subject! Here are some of our findings…
Benefits of a PhD in Data Science
In a PhD program, you’ll have the opportunity to:
- Research an area in data science that may a) be about to the change the industry b) have unexpected applications c) solve a long-standing problem.
- Collaborate with “star” academic advisors in well-funded data science institutes and centers.
- Become a critical thinker—knowing when, where, and why to apply theoretical concepts.
- Specialize in an upcoming field (e.g. biomedical informatics).
- Gain access to massive, real-world data sets through university partnerships.
- Work with cutting-edge technologies and systems that may not be available in the private sector.
- Automatically earn a master’s degree on your way to completing a PhD.
- Qualify for high-level executive or leadership positions.
Downsides of a PhD in Data Science
On the other hand, you should realize that a PhD program:
- Takes 4-5 years on a full-time schedule to complete. These are years when you could be earning money and learning real-world skills in a major company.
- Can be prohibitively expensive if you don’t find ways to fund it.
- May focus too much on pure theory and not enough on pragmatic applications & practical experience.
- Contains a lot of solitary hours in reading and writing. If you want to work with a team or collaborate with industry partners, choose your program & dissertation topic very carefully.
- Won’t give you “on-the-job” knowledge of problems and demands in the corporate world.
As a former PhD student (albeit not in data science), the most important piece of advice I can give you is to pick the right advisor. This is the person who will guide your research, help you with funding, connect you to opportunities & resources, keep you on track, and launch your career. Make people a top priority when considering programs.
Do You Need a PhD to Land a Job?
In most cases, the answer is “no.” In the past, companies had a habit of demanding a PhD in Statistics or Computer Science for top-level positions. This was often because there weren’t many master’s programs in data science and employers wanted reassurance that candidates knew their stuff.
That situation has changed. Because master’s programs now emphasize hard skills & real-world applications, the number of job listings requiring a PhD is dropping rapidly.
Our best advice is to pay attention to the employer and the job title:
- Companies & labs that specialize in data science, and major tech players like Amazon and Facebook, will have a reason for specifying a PhD in the education requirements.
- Other industries may be happy with a strong BS or MS degree and relevant work experience. If you know how to analyze results, make product decisions, increase efficiencies, predict trends, and provide insights, you’re in good shape.
Have a look at the debate on Quora if you’d like more perspective on this question.
Careers for Data Science PhD Holders
PhD holders find careers in academia, industry & university research labs, government departments, and big-name tech companies. These are places that need job candidates who can:
- Research & develop new methodologies.
- Build core products, tools & technologies that are based on data science (e.g. ML or AI algorithms for Google or the next generation of big data management systems).
- Reinvent existing methods & tools for specific purposes.
- Translate research findings & adopt theory to practice (e.g. evaluating the latest discoveries & finding ways to implement them in the corporate world).
- Design research projects for teams of statisticians and data scientists.
Sample job titles include:
- Director of Research
- Senior Data Scientist/Analyst
- Data/Analytics Manager
- Data Science Consultant
- Laboratory Researcher
- Strategic Innovation Manager
- Tenured Professor of Data Science
- Chief Data Officer (CDO)
Typical Program Structure
Data science PhDs are built on the same structure as most doctoral programs. That means you’ll typically have to:
- Complete 2 years of full-time coursework.
- Pass a comprehensive exam—often both oral and written—that shows you have mastered the subject matter.
- Submit a dissertation proposal and have it approved.
- Devote 2-3 years to conducting independent research & writing a dissertation. You’ll probably be teaching undergraduate classes at the same time.
- Defend your work in a “dissertation defense”—usually an oral presentation to academics and the public.
During these years, you can improve your career prospects by attending and speaking at conferences, applying for summer fellowships, consulting, and/or doing paid work for employers (e.g. part-time research).
PhD students are expected to make a creative contribution to the field of data science—that means you’re not allowed to go over old ground or rehash what’s already out there. Your contribution will be summed up in your dissertation, which is a written record of your original research.
Some students go into a PhD already knowing what they want to research. Others use the first couple of years to explore the field and settle on a dissertation topic. Your advisor will be your closest ally in this process – one of the many reasons to choose him/her wisely!
Data Science vs. Business Analytics vs. Specialties
Doctoral programs in data science can also fall under the heading of Statistics, Computational Sciences, Informatics, and the like. Because there’s really no rhyme or reason to the title, evaluate each program on its curriculum instead. Make sure the foundation courses and electives will prepare you for the research area that you want to explore.
The exception to this rule? The PhD in Business Analytics (or Decision/Management Sciences). These programs are typically administered through the School of Business, which means the curriculum often includes corporate topics like management science, marketing, customer analytics, supply chains, etc.
Interested in a particular subset of data science? Some universities are developing specialty PhD programs. Biostatistics and Biomedical/Health Informatics are obvious examples, but you’ll also find a number of doctoral programs in Machine Learning (usually run by the Department of Computer Science) and sub-specialties in fields like Artificial Intelligence and Data Mining.
As always, look for super-smart advisors and find out what’s happening in their research labs!
Typical Admissions Requirements
PhD candidates have to fill out a lengthy application form and pay an application fee. Universities usually want to see applicants who have:
- A Bachelor of Science (BS) in Computer Science, Statistics, or a relevant discipline (e.g. Engineering) with an official transcript from an accredited institution
- A GPA of 3.0 or higher on a 4.0 scale
- GRE test scores
- TOEFL or IELTS for applicants whose native language is not English
- Letters of recommendation
- Statement of purpose/intent
- Résumé or CV
If you don’t already have certain skills (e.g. stats, calculus, computer programming, etc.), the university may ask you to complete prerequisite courses.
In the 2017-2018 academic year, many universities were charging between $1,300-$2,000 per credit hour. With a PhD of 70-75 credits, you could be looking at tuition costs that exceed $150,000. On top of that, you’ll have to pay various fees (e.g. lab, health insurance, technology, international student, etc.).
That’s the bad news. The good news is data science is a high-demand field, so almost all universities will help you cover tuition & living costs. The PhD in Big Data program at Brown, for instance, guarantees five years of financial support—including a stipend and health insurance—to students in good academic standing.
One last thing to consider is your “cost of living” expenses (e.g. housing, books & supplies, food, transport, conference travel, etc.). Does the university provide subsidized housing for PhD students? Can you cover rent with your stipend? Do you mind eating packaged noodles? Use Sperling’s Best Places to compare costs in multiple cities.
How to Pay for a PhD
Your first stop should be the PhD program page on the university website. Here you’ll find links to relevant fellowships and advice on financial matters, including:
- PhD Fellowships: These are scholarships by any other name and they’re usually service-free (i.e. you don’t have to work for them). You’ll find lots of fellowships sponsored by the university, by companies or industries, and by the government (e.g. National Science Foundation). Be aware that some external fellowships will only cover the years of your dissertation research.
- Teaching/Research Assistantships: Assistantships are a popular way for universities to fund PhD students. In return for teaching undergraduates or working as a researcher, you’ll often receive a break on tuition costs and a living stipend.
- In-State Tuition: Public universities (e.g. University of North Carolina) usually offer in-state students a much lower cost per credit. This can be a real boon if you live near a strong school.
- Regional Discounts: Many universities have agreements to offer reduced tuition costs to students from neighboring states (e.g. New England Board of Higher Education Regional Student Program (RSP)). Check to see if this applies to your PhD.
- Travel Grants: It’s important for doctoral students to attend research conferences and network with future collaborators, and a lot of grants are designed with this purpose in mind.
- Student Loans: Consider all your other options before going into debt! A doctorate is a long-term commitment—you may not see a financial return on your education investment for good number of years.
Remember, a lot of PhD students in data science are fully funded. Just to take a few examples:
- Most students in Johns Hopkins University’s PhD in Machine Learning are fully funded through a mixture of research assistantships, teaching assistantships, training grants, and fellowships.
- U.S. citizens and permanent residents in Stanford’s PhD in Biomedical Informatics are funded by a National Library of Medicine (NLM) Training Grant and Big Data to Knowledge (BD2K) Training Grants.
- Warwick University in the U.K. offers approximately 10 fully funded 4-year scholarships to U.K. residents and eligible E.U. students.
If you’re coming from overseas, be sure to talk to your school about any differences between funding for citizens and international students.
Online vs. On-Campus Data Science Programs
Distance education is tempting if you can’t afford to move, and a small number of universities now offer online PhDs in data science. These programs often require you to attend a few campus events (e.g. symposiums), but allow you to complete coursework and conduct research in your own hometown.
We advise you to think very carefully about online learning. It may be a great option if you’re a seasoned pro in San Jose with access to state-of-the-art facilities, fabulous research sources, and on-the-ground mentors. It may not be so great if you live in rural Wyoming.
6 Questions to Ask Yourself Before You Commit
- Are you extremely passionate about an area of research?
- Do you know which academic(s) you want to work with? Are they willing to work with you?
- Do you mind committing to 4-5 years of study when you could be working full-time instead?
- Does your university have strong funding sources (private & government) for data science research?
- Will you have access to super-cool data resources, labs, and industry partners?
- Do you know how you’re going to pay for it?
If you’ve answered “no” to any of these questions, you may wish to reconsider your decision. Trust us, it’s going to be a long haul!
We found 58 universities in our directory offering doctorate-level programs in data science. If you represent a university and would like to contact us about editing any of our listings, or adding new programs, please send an email to info (at) mastersindatascience.org.
PhD in Data Science/Analytics Online
Click here to see the full list of on-campus programs instead.
Colorado Technical University
Students in Colorado Technical University's program leading to a Doctor of Computer Science with a concentration in Big Data Analytics can complete most of the coursework online. However, during their course of studies they must attend at least four residential symposiums at the campus in Denver, which are offered four times per year. First-term students must also attend an on-campus orientation, which is scheduled in conjunction with a symposium. The three-year program requires students to complete 96 credits, and to research, write and defend a dissertation. Applicants should have a master's degree with a GPA of at least 3.0, although CTU also offers the option of earning an accelerated master's degree while starting work on the doctoral degree in a program called the Doctoral Advantage.
Dakota State University
Students earning a Doctor of Science in Information Systems at Dakota State University choose from three research specializations: analytics and decision support, health care information systems, or information assurance and computer security. Students in the online degree program must complete 27 credits in master's level IS courses, 27 credits in the area of specialization, nine credits in research methods, and 25 credits in the dissertation. Candidates also must present a portfolio and pass an exam. Applicants must have at least a bachelor's degree with a GPA of 3.0. Applicants with a master's in information systems can waive the master's level classes. All applicants must submit GRE scores and must know the fundamentals of business and information systems. Program entry is offered in the fall.
Indiana University Bloomington
Doctoral students at Indiana University Bloomington can minor in Data Science, gaining skills that are valuable in fields such as education, business, environmental science, public heath, political science, and sociology. In data science classes, student learn to analyze, visualize and report on large amounts of data. To achieve the doctoral minor in data science, students must complete at least 12 credits of data science coursework, selected in consultation with an adviser from the data science program. Candidates must complete each data science course with a grade of B or better. There is no requirement for a written qualifying exam in a minor field.
Johns Hopkins University
The Bloomberg School of Public Health at Johns Hopkins University offers a DrPH in Health Policy and Management with a public health informatics track. The program is designed for public health professionals and students who have a master's degree in a related field. The program is intended for part-time students, and students have up to nine years to complete the program, which requires at least 64 term credits and a dissertation. Applicants must have a master's degree, at least three years of experience in relevant public health work, and a variety of prerequisite courses, including three courses in statistical methods in public health and a course in principles of epidemiology. Applicants must submit GRE or GMAT scores.
University of North Texas
The University of North Texas has a Ph.D. in Information Science that allows students to concentrate in health informatics. The curriculum for the program includes 12 credits in core areas, 12 credits in required classes in the health informatics concentration, electives in the concentration, and 24 credits in research including a dissertation. Applicants must submit applications to the Toulouse Graduate School and to the Department of Information Science. Applicants must have a master's degree with a 3.5 GPA. The application packet for the Department of Information Science must include GRE scores, a personal statement covering research interests and accomplishments, CV, and three recommendations.
PhD in Data Science/Analytics On-Campus
Click here to see the full list of online programs instead.
Arizona State University
The College of Health Solutions at Arizona State University in Tempe offers a Ph.D. in Biomedical Informatics that allows students to focus on areas such as bioinformatics or clinical informatics. The curriculum requires 84 credits, including 22 core credits, 38 elective credits, 12 credits in research, and 12 in the dissertation. Applicants should have a bachelor's degree with a 3.0 GPA for their last 60 credits or a master's with a 3.0 GPA. The degree should be in a related field such as biology, computer science, statistics, or engineering or the applicant should have training in a field such as nursing or pharmacy. All students must meet prerequisites in anatomy and physiology, calculus, computer programming, biology, and statistics. Students enter the program in the fall.
Students earning a Ph.D. in Business from Bentley University can specialize in business analytics. The program is housed in the Department of Mathematical Sciences, which has a focus on applied research relevant to business. The Ph.D. program requires four years, with two years of coursework and two years when candidates teach one course per semester and work on their dissertation. Applicants should have a master's degree, although the program sometimes accepts students with just a bachelor's degree. Applicants whose degree is not in business must demonstrate their understanding of business subjects. The program prefers students with professional work experience. Applicants must submit GRE or GMAT scores and a five-page research paper outlining their proposed research topic. New students enter in the fall of odd-numbered years.
The School of Public Health at Brown University offers a Ph.D. in Biostatistics for individuals interested in leading interdisciplinary research projects in the fields of public health, medicine, or social sciences. During their doctoral studies, students must complete required coursework, teaching, research, and a dissertation. Applicants can have a bachelor's degree in any field but they must have completed three semesters of calculus, as well as advanced undergraduate courses in linear algebra and probability. Experience with numerical computing is recommended. Applicants must submit GRE scores, three recommendations, and personal statement. Transcripts should indicate a history of academic excellence. Doctoral students begin the program in the fall.
The Ph.D. in Computer Science program at Brown University is interested in students who want to conduct research in data science, big data, and next-generation data management systems. To advance to candidacy, students must pass a programming requirement, coursework requirements, and complete a research project. All students must also train as teaching assistants for at least one semester. As candidates, they must complete a depth requirement and complete and defend a dissertation. Applicants are required to submit GRE scores, letters of recommendation, a statement of purpose, and transcripts. Other factors that can strengthen an application packet include work experience, research experience, awards, and previous high academic performance in STEM subjects. New students enter the program in September.
California Institute of Technology
CalTech has a new Ph.D. in Computing and Mathematical Sciences that is multidisciplinary and brings together faculty and students from fields including computer science, electrical engineering, applied math, operations research, economics, and the physical sciences. In their first year, all students take courses in math and computing fundamentals, and each student must take three courses in a focus area and meet breadth requirements. All candidates must complete a dissertation. Applicants should be interested in an interdisciplinary field, and those accepted generally received an undergraduate degree in math, computer science, electrical engineering, or economics. Applicants must submit general GRE scores, and the college advises submitting scores from a subject test as well. Students enter the program in the fall.
Carnegie Mellon University
The Ph.D. in Machine Learning program at Carnegie Mellon University is sponsored by the School of Computer Science and Department of Statistics. This is a five-year program that requires students to complete core courses, electives, and a data analysis project for a master's degree; gain proficiency in teaching, research, and conference presentation; and complete a thesis. Applicants must have at least a bachelor's degree and must submit GRE scores. The program does not list any specific desired undergraduate majors but students who are admitted must be proficient in linear algebra, probability, and proofs and be highly skilled in computer programming. Carnegie Mellon provides funding for machine learning Ph.D. candidates for five years of study.
Chapman University offers a Ph.D. in Computational and Data Sciences that students can complete in about four years of full-time study, but the program also accepts individuals interested in part-time study. The curriculum requires 70 to 73 credits, including 10 to 13 core credits, 45 credits in electives and research, and 12 credits for the dissertation. Applicants must have a bachelor's degree and must submit GRE scores. Prerequisite courses are differential equations, data structures, and probability and statistics. Accepted student who do not meet those prerequisites are required to take foundation courses. The college will accept up to 30 credits from a master's program. Students begin the program in the fall.
Clemson University and the Medical University of South Carolina jointly offer a Ph.D. in Biomedical Data Science and Informatics. The program has three specialty tracks: precision medicine, population health, and clinical and translational informatics. Students must complete 65 to 68 credits in coursework and a dissertation. Coursework is in five areas: biomedical informatics; computing, math, statistics, and engineering; population health, systems, and policy; biological and medical; lab rotations, seminars, and doctoral research. Applicants must have a bachelor's degree in math, statistics, health sciences, or engineering. Prerequisites include a year of calculus, a year of college biology, and an advanced computer programming course. GRE scores are required. Most students are expected to complete the degree in five years or less.
Columbia University in the City of New York
Columbia University has a Ph.D. in Biomedical Informatics that is offered as a full-time program. Students spend about two to three years completing coursework before focusing on independent research. In addition, students in the program are required to perform as teaching assistant for two courses, submit papers and posters to national conferences, attend conferences, pass two oral exams, and complete a dissertation. All students in this program are fully funded. The program is open to students who have at least a bachelor's degree in a discipline such as math, computer science, nursing, medicine, pubic health, information management, physics, or biology. Applicants must submit GRE scores, personal statement, three recommendations, resume, and official transcripts. Students start the program in the fall.
Dartmouth University offers a Ph.D. in Quantitative Biomedical Sciences that provides a strong foundation in areas such as bioinformatics, biostatistics, and epidemiology. In addition to coursework, students must take part in research rotations in which they work on research with faculty members, supervised teaching, a weekly journal club, a qualifying exam, research, and a dissertation. Applicants should have a background and academic degree in a quantitative area such as biology, epidemiology, bioinformatics, math, or computer science. Students who have not taken adequate undergraduate courses in related topics will be required to complete deficiency coursework in their first semester. The program is open to full-time students, and the university provides fellowship funding for all students in the program.
George Mason University
The Ph.D. in Computational Sciences and Informatics at George Mason University is a 72-credit program that requires a dissertation. All students must select a focus area from either data science or computer modeling and simulation. Students who have completed a master's in computational science or a similar field may be able to eliminate up to 24 required credits. The program is designed for part-time students, with courses offered in the late afternoon or early evening. Applicants should have at least a bachelor's degree in a STEM field with a GPA of 3.0 or higher. They must have completed math coursework through differential equations and must know a computer programming language. GRE scores are required for applicants without a master's degree.
Georgia State University
Georgia State University's Department of Computer Science has a Ph.D. in Computer Science program that offers a bioinformatics concentration. Requirements for the degree include completing 48 credits of graduate coursework, which must include three courses in bioinformatics, three in biology, one in chemistry, and one in biostatistics. Candidates must also pass a candidacy exam and complete a dissertation. Applicants must have, at minimum, a bachelor's degree in computer science or a related field with a GPA of 3.0 or higher. Students whose background is not in computer science will have to complete foundation work before beginning work on the doctorate. Applicants must submit GRE scores, three recommendations, and a personal statement. Students may only enter the Ph.D. program in the fall.
Indiana University-Purdue University-Indianapolis
The School of Informatics and Computing at IUPUI recently introduced a program leading to a Ph.D. in Data Science. To earn the degree, students must complete 24 credits in data science core courses, 18 credits in methods courses, a minor appropriate to their chosen specialty with all courses taken from outside the data science program, and 30 credits in a dissertation. Applicants must have at least a bachelor's degree with a 3.0 or higher GPA. However, most admitted students have a master's degree in a field such as data science, computing, health, or a social science with a GPA of 3.5. GRE scores are required, with admitted students typically scoring above the 70th percentile. The doctoral program requires students to start in the fall.
The School of Informatics and Computing at IUPUI offers a Ph.D. in Health and Biomedical Informatics for students interested in working for health care agencies, insurance companies, or related organizations. This 90-credit program requires students to complete a minor that aligns with the subdiscipline of informatics they are interested in. Typically, students can complete the degree in about four years, including some summers. Applicants should have a bachelor's degree with an undergraduate GPA of 3.0 or higher. Accepted applicants usually have a degree in a technical field such as math, engineering, computer science, or statistics, or in a health-related field such as biology, biochemistry, or nursing. All applicants should have completed coursework in a programming language, databases, medical terminology, anatomy, and physiology.
Iowa State University
Iowa State University's Ph.D in Bioinformatics and Computational Biology has a strong research focus. In their first year, all Ph.D. students must participate in research exploration rotations in which they work in three different professors' labs. Typically, students can complete the courses, research, and thesis requirements for the program in about five years. Applicants should have a bachelor's degree in molecular biology, computer science, math, statistics, physics, or a closely related field. The undergraduate GPA should be 3.3 or higher, and applicants should be in the upper quarter of their college graduating class. GRE scores are required. First-year students should expect to take some background coursework. Prerequisites include three calculus courses, probability and statistics, genetics, biological evolution, data structures, and object oriented programming.
Jackson State University
Jackson State University offers a Ph.D. in Computational and Data-Enabled Science and Engineering that has a concentration track in Computational Mathematics and Statistical Science. To earn the degree, students must complete 12 credits in a common core, 12 credits in core concentration track courses, 24 credits in concentration electives, and 24 credits in a dissertation. Applicants should have a bachelor's or master's degree in a STEM field or another closely related field, as long as they have a strong computational and quantitative background. Applicants must have attained a GPA of 3.0 or higher on the highest degree they have earned. GRE scores, statement of purpose, and three recommendations are required. JSU has several funding opportunities for doctoral students.
Johns Hopkins University
Johns Hopkins University has a Ph.D. in Health Sciences Informatics geared toward individuals who want to become researchers in health informatics. The program requires students to complete 125 quarter credits, including core courses, electives, practicum and research rotations, and mentored research. The requirements are spread over several learning areas, including biomedical informatics, computer science, research, clinical informatics, public health informatics, and practical experience. Applicants with a bachelor's degree are required to submit GRE scores or have at least five years of professional experience in a relevant field, such as medicine, dentistry, nursing, public health, bioengineering, or computer science. Applicants with a master's or Ph.D. do not have to submit GRE scores or provide relevant experience. Students enter the program in the fall.
Students interested in machine learning can earn a Ph.D. in the field at Johns Hopkins University through one of the departments involved in the cross-departmental interest area. Relevant departments include computer science, applied math and statistics, biostatistics, biomedical engineering, cognitive science, and electrical and computer engineering. Students can take coursework from multiple departments and choose dissertation committee members from a variety of departments. Applicants should apply for admission to the department that is most closely related to their interests or educational background. Degree requirements may vary by department. Applicants must submit GRE scores, and some departments, such as math, require the GRE subject test as well as the general test. Doctoral programs start in the fall.
Kennesaw State University
The Ph.D. in Analytics and Data Science from Kennesaw State University has a strong focus on application, with all candidates required to engage with sponsoring organizations, including completion of a doctoral internship. The 78-credit program includes 48 credits in core coursework: 24 credits in statistics, nine credits in math, and 15 credits in computer science. Students must pass a comprehensive exam on those subject areas. Applicants to the program should have a master's degree in a computational field such as statistics, math, engineering, computer science, or finance and must submit GRE scores. Prerequisites include successful completion of two semesters of calculus, programming experience, and supervised modeling experience. While not required, KSU recommends applicants have Base SAS Certification.
New York University
NYU's Tandon School of Engineering offers a Ph.D. in Computer Science where students can benefit from the school's research strengths in visualization, databases, and big data. To earn the doctoral degree, students must complete at least 75 credits beyond a bachelor's degree, including a Ph.D. thesis. Students may transfer up to 30 credits from a master's program. Applicants must have at least a bachelor's degree in computer science or a closely related field, such as computer engineering. Potential students with a bachelor's degree in a different field are advised to earn a master's in computer science before applying. Applicants must submit GRE scores. The program accepts full-time students only, and they enter in the fall.
The NYU School of Medicine offers a Ph.D. in Biostatistics that has an interdisciplinary focus and covers a broad range of research areas. Candidates collaborate with faculty in a variety of studies. Students must attend full-time and complete 32 credits of coursework and 40 credits in research and seminar work. Additional requirements include passing a qualifying exam, submitting one research article to a peer-reviewed journal, and a thesis. Applicants should have a background in statistics or math and biology and must have at least a bachelor's degree. Admission decisions are based on research experience, academic achievement, recommendations, scientific potential, and GRE scores. Applicants who advance past initial screening may be interviewed. Students typically complete the program in less than six years.
NYU offers a Ph.D. in Data Science that requires students to complete 72 credits in coursework as well as a dissertation. The curriculum includes five required courses, for 15 credits, with the rest of the credits earned through electives. Students who are admitted to the program are guaranteed funding for two semesters a year for up to five years. Applicants must have at least a bachelor's degree in a relevant field such as math, statistics, computer science, or engineering. Individuals with work or research experience in data science are also welcome to apply. Applicants must have coursework in calculus, probability, statistics, and programming, and they are required to submit either GRE or GMAT scores. Only full-time students are accepted.
The NYU School of Medicine has a program leading to a Ph.D. in Systems & Computational Biomedicine. Candidates in the program have access to a high-performance computing facility, research labs, and other advanced facilities. Students spend their first year in research lab rotations before committing to a training track, and candidates work with their mentor to select coursework appropriate to their experience and goals. All students complete independent research and a dissertation. Applicants must have a bachelor's degree and should have a strong background in a field such as math, biology, chemistry, or physics. Applicants must submit GRE scores. Admission decisions are based on research experience, academic achievement, recommendations, scientific potential, and GRE scores. Applicants who advance past initial screening may be interviewed.
Newcastle University's Digital Institute offers a CDT in Cloud Computing for Big Business, a program leading to doctoral training. Students spend the first six months doing classwork and a group project at the master's level before moving to the doctoral program, where they will conduct research, get additional training, and take part in research retreats. During their second and third years, students may take a placement with business, industry, or an academic partner. The program is designed primarily for applicants with a background in computing or statistics, although applicants with a quantitative background such as physics or engineering may be admitted. Applicants must have the equivalent of a Honors Degree and must submit a CV and personal statement.
North Carolina State University at Raleigh
Northeastern University offers a Ph.D. in Personal Health Informatics that combines coursework in computer science, design, and health to create research leaders. The curriculum requires at least 48 credits of graduate level coursework. Students must take part in a usability evaluation practicum and in a team project to design, develop, and evaluate a wellness or health interface technology. Including dissertation, the program takes about five years to complete. Applicants should have a bachelor's degree in a technical field such as computer science or in a health science discipline. Applicants without a technical background should take programming courses before starting work on the degree. Applicants should have a 3.0 or higher GPA and must submit GRE scores. Students enter the program in September.
Oregon Health & Science University
OHSU's Ph.D. in Bioinformatics & Computational Biology is designed for individuals interested in research, academia, or the health care industry. Students must complete at least 135 credits, including 42 credits in biomedical informatics, 12 in a cognate area, 12 in advanced research methods, eight credits in mentored teaching, and 48 in research and dissertation. Students may be able to transfer up to 45 credits earned in formal coursework from another institution. Applicants must have a bachelor's degree with a GPA of 3.0 or higher. While OHSU doesn't specify an undergrad major, applicants must have completed courses in biology, computer programming, genetics, and statistics or biostatistics. Courses in biochemistry are recommended but not required. GRE scores are required. Doctoral students begin the program in the fall.
The Ph.D. in Biomedical Informatics program at Oregon Health and Science University has a bioinformatics & computational biology track that is designed for students interested in bioinformatics research, teaching, and analysis. This is an interdisciplinary program that also requires students to develop a depth of knowledge in a cognate area. To earn their doctorate, candidates must complete 135 credits, including 48 credits in biomedical informatics, 12 in advanced research methods, 12 in the cognate area, and 48 in research and dissertation. Prerequisites for this program included courses in biology, computer programming, statistics or biostatistics, and genetics. A course in biochemistry is recommended but not required. Applicants must have a bachelor's degree with a minimum GPA of 3.0. Students enter the program in the fall
Oregon Health and Science University has a Ph.D. in Biomedical Informatics that allows students to pursue a clinical informatics track. All students in this track must select a cognate area for in-depth training, such as public health, computer science, biomedical engineering, or nursing. Cognate classes can be taken at OHSU or Portland State University. The curriculum requires at least 135 credits, including 48 credits in biomedical informatics, 12 in the cognate area, 12 in advanced research methods, and 48 in research and dissertation. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher. Prerequisites include anatomy and physiology, computer science, and statistics. Applicants must submit GRE scores, three recommendations, personal statement, transcripts, and resume.
Students in the Ph.D. in Biomedical Informatics program at Rutgers University School of Health Professions have a choice of specializations: nanomedicine and clinical informatics; consumer/patient care informatics; bioinformatics; or hospital/health care management informatics. Full-time students can complete the 61-credit program in three to five years, and part-time students have up to 10 years to complete the requirements. Students must complete eight courses, a qualifying exam, and a dissertation. Applicants must have a master's degree from an accredited university in one of the health sciences, such as medicine or nursing, biological sciences, computer science, engineering, or an equivalent field. Applicants are not required to submit GRE scores, but official transcripts, personal statement, CV, and three recommendations are required.
South Dakota State University
The Ph.D. in Computational Science and Statistics program at South Dakota State University is research intensive, but coursework if flexible so students can customize the curriculum to support their research interests. Students must complete 60 credits beyond the master's, or 90 beyond the bachelor's degree. Applicants must have a master's degree, with math or statistics the preferred degrees. Students with a master's in a closely related field, such as computer science, economics, or biological sciences, should have a taken math through linear algebra and differential equations, a calculus-based statistics course, and should be proficient in a computer programming language. Standardized test scores are not required. Students enter in the fall, and some students can complete the program in three years.
The Ph.D. in Biomedical Informatics program at Stanford University has a strong emphasis on development of methods, unlike many programs that are more focused on application. This is a full-time, residential, research-oriented program with no option to attend part time or through distance education. Students generally complete the program in about five years. Applicants must have at least a bachelor's degree, although many applicants have advanced degrees. Prerequisites include at least one year of calculus, but multivariate calculus is recommended; probability and statistics; linear algebra; a year of computer programming or computer science; and a year of college biology. Applicants must submit GRE scores, resume, transcripts, and recommendations. Students enter the program in the fall term.
Students interested in biostatistics can earn a Ph.D. in Statistics with a concentration in biostatistics from Stanford University. Another option is a specialized concentration for the Ph.D. in Statistics program called the Training Program in Biostatistics for Personalized Medicine, an interdisciplinary program with input from faculty in fields as diverse as genetics, computer science, statistics, and medicine. The personalized medicine program requires core coursework in statisitics, as well as personalized medicine coursework, mentored research, and an internship in a research lab. Applicants should have a strong math background and are required to submit GRE Math subject test scores as well as GRE general test scores. The application packet must include statement of purpose, transcripts, three recommendations, and resume.
The University of Tennessee
The Haslam College of Business at the University of Tennessee in Knoxville offers a Ph.D. in Analytics as a concentration in its Ph.D. in Management Science program. Students must complete 33 credits in core coursework plus a dissertation. Applicants who do not have an adequate background in business analytics must take 15 credits in prerequisites before starting the program, resulting in 48 required credits. The program uses a cohort format, with a new cohort entering the program each fall. Applicants must have at least a bachelor's degree. The program does not require any specific undergraduate major but looks for students with a quantitative background, including classes in calculus, math, and statistics. Successful applicants have a GPA over 3.0. GRE or GMAT scores are required.
The University of Texas at Dallas
The Ph.D. in Geospatial Information Sciences at the University of Texas at Dallas is a cross-disciplinary program focused on developing researchers. The program is offered jointly by three schools at UT: School of Economic, Political and Policy Sciences; School of Natural Sciences and Mathematics; and the Erick Jonsson School of Engineering and Computer Science. Applicants must have a bachelor's or master's degree in a discipline related to GIS, such as geography, geology, computer science, statistics, economics, urban planning, or natural resource management. Applicants should have a GPA of at least 3.25, and they must submit GRE or GMAT scores. Prerequisites include calculus, proficiency in a programming language, and a course in inferential statistics.
The University of Texas Health Science Center at Houston
The Ph.D. in Biomedical Informatics program at the University of Texas is a full-time, on-campus program open to students with various backgrounds. The curriculum requires 93 credits, including required and elective courses, a qualifying exam, 21 credits in a specific research area in biomedical informatics, and a dissertation. Prerequisites include an introductory course in biomedical informatics as well as at least one course each in statistical methods, data structure and algorithms, and research design and evaluation. Applicants must have a bachelor's degree or higher. UT does not set a minimum GPA, but most admitted students have a GPA of 3.0 or higher. Applicants must submit GRE scores, resume, three references, and goal statements. Students may enter the program in the fall, spring, or summer.
Tulane University of Louisiana
The School of Public Health and Tropical Medicine at Tulane University offers a Ph.D. in Biostatistics that prepares students to develop and evaluate new data science and biostatistical methods. Students must complete at least 72 post-baccalaureate credits, and up to 42 credits from master's work can be applied. Students without a background in public health must remedy that deficiency. The program includes required courses in math, biostatistics, and epidemiology. All students must complete a comprehensive exam and conduct original research for a dissertation. Applicants should have a master's degree in biostatistics or a closely related field with a 3.5 GPA. Prerequisites include one year of college calculus, including multivariate calculus, and a course in linear algebra. GRE scores are required.
University at Buffalo
The Ph.D. in Computational and Data-Enabled Science and Engineering from the University at Buffalo requires students to complete 72 credits. Core coursework, worth 30 credits, includes classes in data science, applied math and numerical methods, and high-performance and data-intensive computing. Students may be able to apply master's credits towards these classes. For additional courses, students can choose offerings from seven departments. Students must also pass an oral exam and prepare a dissertation. Applicants for this program must have a master's degree in a related field, such as engineering, math, physics, business, or pharmacy. They must have a GPA of 3.0 or higher on previous work and must submit GRE scores and letters of recommendation.
University of Arkansas at Little Rock
Students at the University of Arkansas Little Rock must complete the Master of Science in Bioinformatics with an A on their capstone project to be admitted to the Ph.D. in Bioinformatics program. Once they earn their master's, bioinformatics students concentrate on research, including preparing a grant request to fund their dissertation research. To enter the bioinformatics program, applicants must have at least a bachelor's degree in statistics, the life sciences, or computer science. Students with other undergraduate majors must take leveling courses. Prerequisite courses include genetics, applied statistics, databases, and object-oriented programming or experience using Java. Applicants should have an undergrad GPA of at least 3.0 and must submit GRE scores, references, letter of intent, and resume.
University of Cincinnati
Students earning a Ph.D. in Biomedical Informatics from the University of Cincinnati become involved in research during their first semester. The curriculum is interdisciplinary and includes content from the colleges of engineering, medicine, allied health sciences, design, and business. Students complete 19 core credits, six credits in medical sciences, 12 credits in technical electives, and 53 credits in a research dissertation. Students can complete the program in eight semesters of full-time study. Applicants should have at least a bachelor's degree with a GPA of 3.5 or higher (or be in the top 10 percent of a highly selective undergraduate program). Preferred majors include biology, bioengineering, math, statistics, or computer science. Applicants must submit GRE scores, statement of purpose, and at least three recommendations.
The University of Cincinnati's College of Medicine has a big data track option for its program leading to a Ph.D. in Biostatistics. Curriculum covers traditional biostatistics coursework, computational coursework, and courses that apply to biomedical research. Students must complete 90 credits, including some electives in big data, and research for a dissertation. Applicants must submit GRE, GMAT, or MCAT scores, which should be at the 50th percentile or higher. They must have at least a bachelor's degree and must submit transcripts from all colleges or universities attended. Other application documents needed include three recommendations, resume, and statement of purpose. Students may be interviewed before a final admissions decision is made. Students can enter the program in the spring or fall.
The Carl H. Linder College of Business at the University of Cincinnati offers a Ph.D. in Operations, Business Analytics & Information Systems that allows students to work on interdisciplinary problems. Students in the program spend up to two years in coursework learning research methods and deep content, create a second-year paper, and take comprehensive exams. They must also produce a dissertation, which typically takes two to three years, resulting in a program that usually takes up to five years of full-time study. The program is not open to part-time students. Applicants must have a bachelor's degree in a relevant field with a B average. Students cab enter the program only in September. Doctoral students are eligible for scholarships and for graduate assistantships in teaching or research.
University of Delaware
The Alfred Lerner College of Business and Economics at the University of Delaware offers a Ph.D. in Financial Services Analytics, which it says is the first program of its kind. Candidates must complete 45 to 54 course credits, pass a qualifying exam covering core curriculum, and prepare a dissertation. Corporate partners offer internships to give students real-world experience. A cohort enters the program once every two years, in the fall of even-numbered years. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher. The undergrad degree can be in any discipline, but substantial coursework in a quantitative subject and hands-on experience in software development are prerequisites. Applicants must submit GRE or GMAT scores, essay, and three recommendations.
University of Idaho
Students in the Ph.D. in Bioinformatics and Computational Biology program at the University of Idaho receive an interdisciplinary education with an emphasis on statistical analysis, computation, and genomics. The curriculum requires 78 credits, including nine credits in core courses, 15 in depth courses, and 30 for research and thesis. For their depth requirements, students choose a focus area: biological sciences or computer science/mathematical sciences. Ph.D. candidates must complete a lab rotation or internship, and they must complete a teaching experience. Applicants must have at least a bachelor's degree from an accredited college. A GPA of 3.0 or higher is preferred, although five years of relevant professional experience is accepted. GRE scores are required. Depending on their background, students may be required to take foundation courses.
University of Illinois at Chicago
The Ph.D. in Biomedical and Health Informatics program at the University of Illinois Chicago has a strong mentorship component, with each candidate assigned two mentors, one for specialized research and one for methodology. This is a full-time program and most courses are delivered face-to-face, with a few courses available online or in a blended format. Prerequisite courses include foundations of health information management, medical terminology, and a computer programming course. Applicants should have a bachelor's degree or higher, and an undergrad GPA of 3.0. GRE scores are required for most applicants. Other required documents include transcripts, personal statement, resume, and three recommendations. Students can complete the program in about four years, depending on the time required for their research and dissertation.
The University of Illinois at Chicago has a Ph.D. in Business Administration with an emphasis in Information Decision Sciences for students interested in areas such as machine learning, data mining, or operations research. To earn the Ph.D., students must complete 96 credits beyond the bachelor's degree (64 credits for students who have a relevant master's degree), including a dissertation. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher for the last 60 credits. The university does not require any specific undergraduate majors, but applicants should have completed courses in math and statistics, computing or analysis, and business. GRE or GMAT scores are required. Students may only enter in the fall.
University of Iowa
Students working towards a Ph.D. in Bioinformatics at the University of Iowa must complete 72 credits, including 21 credits in core coursework that covers bioinformatics, biology, informatics, and genetics. Additional requirements include courses in statistics, ethics seminars, and elective courses. Candidates must also pass a comprehensive exam and complete a dissertation. Applicants must have at least a bachelor's degree with a minimum GPA of 3.0. However, the bioinformatics program does not require any specific undergraduate major and does not have any prerequisite classes. Applicants must submit transcripts of prior college work, statement of purpose, resume, and three recommendations. Students enter the program in the fall, and they typically earn their doctorate in about five years, depending upon their area of research.
Students earning a Ph.D. in Informatics - Health Informatics from the University of Iowa select a focus area and concentrate most of their coursework there. The doctorate requires students to complete 72 credits, including 18 in core health informatics coursework. For the remaining 54 credits, students work with their adviser to select appropriate focus coursework. Candidates must also pass a comprehensive exam and complete a dissertation showcasing original research. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher. Applicants must submit standardized test scores, and for health informatics, GRE, MCAT, or PCAT scores are accepted. The application packet must include transcripts, statement of purpose, three recommendations, and resume. Students enter the doctoral program in the fall.
Students earning a Ph.D. in Management Sciences from the University of Iowa can choose from three specialization areas: information systems, quantitative methods, or operations management. The program requires 72 credits, plus a dissertation. The flexible study plan allows students to take electives in any year, and students typically complete the degree in five years. Applicants should have a technical background in a field such as math, computer science, or engineering. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher. GRE or GMAT scores are required. Students enter the program in the fall, and the university provides Ph.D. candidates with funding for at least four years. Candidates are required to serve as research or teaching assistants.
University of Kansas
Students earning a Ph.D. in Biostatistics from the University of Kansas can typically complete the requirements in four years. The requirements include 63 credits in coursework and a collaborative research experience, annual evaluations, graduate exams, and a dissertation. Students who already have a master's in biostatistics might not need to complete all the coursework. Applicants should have a master's degree in statistics, biostatistics, math, or applied math with an undergrad GPA of at least 3.0. GRE scores are required. Prerequisites include three semesters of calculus with a grade of B or higher; a course in a computer programming language; and a course in differential equations, linear algebra, or numerical analysis. Research experience is strongly recommended. All applicants will be interviewed in person or via Skype.
University of Maine
Students seeking a Ph.D. in Spatial Information Science and Engineering from the University of Maine face a minimum residency of two academic years. The program requires 42 credits in coursework beyond a bachelor's degree. Typically, students already have a master's, but applicants without a master's may enter the program. This is a research program that requires a thesis, and students must complete a minor outside of spatial information science. Applicants must have at least a bachelor's degree with a GPA of 3.0 or higher. Preferred degrees are in engineering, computer science, math, geography, or cognitive science. Students should have a strong technical background. The minimum math requirement is college algebra, and the college recommends courses or experience in programming. Applicants must submit GRE scores.
University of Maryland-College Park
Students in the Ph.D. in Information Studies program offered by the College of Information Studies at the University of Maryland can take part in research in a variety of areas, including big data, data science, and informatics. The program is designed for students who want a research-oriented career, and faculty members mentor students in a variety of disciplines. Applicants are required to submit GRE scores, resume, three recommendations, transcripts, and a statement of purpose covering research interests, relevant skills, and goals. The program does not list any specific prerequisites for the doctoral program, and the interdisciplinary program accepts students with varied academic backgrounds. Full-time and part-time students are accepted. Students enter the program in the fall.
University of Massachusetts-Boston
The College of Management at the University of Massachusetts Boston offers a Doctor of Philosophy in Business Administration degree with an information systems for data science track. While it is possible for students to request some required courses to be waived based on prior studies, all students must complete at least 14 courses to be eligible for graduation. The first two years of the program consists of coursework; the remaining time of enrollment is spent on research related to a student's dissertation topic. PhD assistantships are available for qualified doctoral candidates. Assistantships include full tuition and fee waivers in addition to a yearly stipend of $25,000 for three years. Most courses meet once a week during late afternoon and evening hours.
University of Michigan-Ann Arbor
The Ph.D. in Statistics program at the University of Michigan provides flexibility so students can pursue the branch of the discipline that most interests them. All students must pass two qualifying tests - one in theory and one in applied statistics - to remain in the program, and a master's degree is embedded in the program. Students can gain consulting experience working with other campus researchers, and all candidates also work as instructors. The college weighs a variety of factors in making admissions decisions, including GPA, grades in STEM coursework, GRE scores, and research accomplishments. All Ph.D. students are guaranteed funding for five years, which is the typical time needed to earn the degree. Students start the program in the fall.
University of Minnesota-Twin Cities
The University of Minnesota's Ph.D. in Health Informatics is designed for students who want a career in research or academia. This is a 70-credit program that requires all students to use their electives to complete either a formal minor or to take related classes outside of the health informatics department. All students must produce a dissertation. Applicants should have a master's degree in a STEM field or a field related to health informatics with a GPA of 3.5. Prerequisites include six semester credits in life or health science coursework and experience or coursework in a programming language. Applicants must submit GRE scores, three recommendations, and a personal statement. Students may only enter the doctoral program in the fall semester.
University of Missouri-Columbia
Students in the University of Missouri's Ph.D. in Informatics program can pursue a Health Informatics emphasis. The program is designed for students who are interested in research or academic careers. All students complete core coursework and then concentrate in an emphasis area. Options include health systems informatics, clinical informatics, consumer health informatics, or public health informatics. Applicants should have a bachelor's degree with a GPA of 3.3 or higher. The program accepts students with a variety of academic backgrounds, but students without the necessary technical or medical background may have to take prerequisite courses. Applicants must submit GRE scores, three recommendations, a CV, and a statement of purpose. Students enter the program in the fall. Some fellowships and assistantships are available.
University of Missouri-Kansas City
The University of Missouri Kansas City offers an interdisciplinary doctorate that requires students to develop an individualized academic plan that covers both a primary discipline and a co-discipline. The Department of Biomedical and Health Informatics permits students to study bioinformatics as a primary discipline or co-discipline. Students who name it has their primary disciple can choose a co-discipline such as math and statistics, pharmaceutical science, cell biology, or computer science. The curriculum includes coursework, comprehensive exams, and a dissertation. Students interested in the interdisciplinary doctorate must submit a general application to UMKC, and supplemental applications to the interdisciplinary Ph.D. program and the School of Medicine. Applicants must submit GRE scores, statement of intent, transcripts, resume, and three recommendations.
University of Nebraska at Omaha
The University of Nebraska Omaha offers a Ph.D. in Biomedical Informatics with two tracks. Students with a background in fields such as anatomy or cell biology follow a health informatics tracks while those with a background in math, statistics, or programming follow a bioinformatics track. To earn their degree, students must complete 90 post-baccalaureate credits. Requirements include core courses, research courses, a major field of study, a cognate field of study, and a dissertation. Candidates must also take part in mentored teaching. Students generally complete the program in four to five years of full-time study. Applicants must have at least a bachelor's degree and should submit publications or other projects that demonstrate their potential. The university requires GRE scores.
University of Nevada-Reno
The University of Nevada, Reno, has a Ph.D. in Statistics and Data Science that emphasizes interdisciplinary collaborative research. This is a 72-credit program, including a dissertation, and students can complete the program in about four years. The program recommends that all entering students have a master's degree in math or statistics; the minimum requirement is a bachelor's degree with a 3.0 GPA. Applicants must submit general GRE scores, and it is recommended that they submit GRE math test scores as well. The application package must also include three recommendations, statement of purpose, and resume. Students may enter the program in the spring or fall semester. All students admitted to this doctoral program receive some funding.
University of North Carolina at Chapel Hill
The University of North Carolina at Chapel Hill offers a Ph.D. in Health Informatics that provides candidates with training in interdisciplinary research and administrative knowledge and also provides experience in teaching. To earn the degree, candidates must complete 55 credits in coursework, comprehensive exams, and a dissertation. Coursework covers foundations of informatics, tools and infrastructure, research methods, project management and academic leadership, and implementation and translation. Applicants must have a bachelor's degree with an undergrad GPA of at least 3.0. Applicants should have an academic background or work experience in health care and statistics or computing. Applicants are required to submit GRE scores, transcripts, resume, three recommendations, and statement of purpose. Students may enter the program in the fall, spring, or summer term.
University of Oklahoma Norman Campus
The Price College of Business at the University of Oklahoma has a program leading to a Ph.D. in Business Administration with a specialization in Management Information Systems that is designed for students who want an academic career. The curriculum includes 47 credits of required coursework, and students without an MBA may have to take up to 21 core MBA credits. Applicants must have at least a bachelor's degree with a GPA of 3.5 or higher. The university does not specify a major, but accepted students are expected to have background courses in linear algebra, differential calculus, integration techniques, and optimization, as well as MBA core courses in economics, management, and financial accounting. Applicants must also submit GMAT scores, resume, and statement of goals.
University of Pittsburgh-Pittsburgh Campus
The University of Pittsburgh offers a Ph.D. in Biostatistics that emphasizes statistical theory and methods and prepares students to work in interdisciplinary studies or to serve as leaders in designing and carrying out studies. Students who are interested in statistical genetics can pursue that training through this program by selecting electives in genetics. The curriculum requires students to complete 72 credits, including courses in the fundamentals of statistical theory and application as well as classes in public health and epidemiology. Students must take part in a statistical consulting practicum and perform dissertation research in a specialized area. Applicants must have at least a bachelor's degree with a minimum of three credits in biology and six credits in calculus. GRE scores are required.
The University of Pittsburgh offers a Ph.D. in Biomedical Informatics that students can complete in four years of full-time study. The curriculum requires students to complete at least 72 credits, including 26 credits in core coursework and 18 credits in the dissertation. Depending upon their background, students may be required to take deficiency coursework in topics such as problem-oriented programming, math for biomedical informatics, patient care, or biology during their first semester. Applicants must submit GRE scores, a personal statement, and transcripts. Students enter the program in the fall. The university also offers an M.D./Ph.D. in Biomedical Informatics for students who have taken some medical school coursework.
The Katz G raduate School of Business at the University of Pittsburgh offers a Ph.D. in Business Analytics and Operations. Students can choose from a wide variety of concentration areas,such as data mining and business analytics, decision sciences, simulation methodology, or stochastic modeling and applied statistical methods. The doctoral program is designed primarily for students who want to perform research or teach. Students can complete the program in four or five years, with the first two years devoted to coursework and the rest to a dissertation. Applicants must submit three recommendations, transcripts and test scores; GMAT scores are preferred but GRE scores are accepted. Students enter the program in the fall, and the program provides all doctoral students funding for up to five years.
Students seeking a Ph.D. in Intelligent Systems from the University of Pittsburgh can pursue a Biomedical Informatics certification. The intelligent systems program is a multidisciplinary program that focuses on applied artificial intelligence and allows students to customize their curriculum. The biomedical informatics track focuses on research and training in medical applications. Interested students must apply both to the intelligent systems program and the biomedical informatics program, which have separate submission procedures. Applicants should have a relevant background such as an undergraduate major in computer science or engineering. Applicants should be proficient in a programming language such as Java or C++. Both departments require students to submit GRE scores, and the intelligent systems department requires three recommendations. Students start the program in the fall.
University of Southern California
The Ph.D. in Data Sciences & Operations program at Marshall University allows students to specialize in statistics or operations management. Students spend their first two years taking courses and developing research skills with the help of a mentor. By the third year, they begin to work on their dissertation, gain teaching skills by working as a teaching assistant, and pass a qualifying exam. In their fourth and fifth years, they complete their dissertation and co-teach a course. Applicants must have a bachelor's degree with a GPA of 3.0 or higher and must submit GMAT or GRE scores. Other required documents include three letters of recommendation, a personal statement, and resume. Students enter the program in the fall.
University of Utah
The School of Medicine at the University of Utah offers a Ph.D. in Biomedical Informatics designed for students interested in research. The curriculum includes about 40 credits in formal coursework, a comprehensive exam, 14 credits in dissertation research, and a dissertation. Some graduate credits previously taken, such as for a master's degree, might be applied toward the doctorate. The Ph.D. program has five core courses, and many are offered in a hybrid format or online. Applicants must have a bachelor's degree with an undergrad GPA of 3.3 or higher. GRE, GMAT, or MCAT scores are required. Prerequisite courses for the program include at least one college level course in a programming language, statistics, and basic biology. Students enter the program in the fall semester.
University of Washington-Seattle Campus
Ph.D. students in seven different departments at the University of Washington can take part in an advanced data science option, known as the IGERT in Big Data and Data Science. This is an interdisciplinary program that connects students with mentors in other, complementary fields. In addition to the Ph.D. requirements in their home department, students who enter the IGERT program must take three core courses and a big data seminar course. They are also required to complete an interdisciplinary research project with an adviser and to complete at least one internship involving practical work with big data. Participating departments include statistics, computer science and engineering, chemical engineering, biology, genome sciences, astronomy, biology, and oceanography.
The University of Washington offers a Ph.D. in Biomedical Informatics that focuses on research. Students must take nine core courses for 34 credits, participate in research seminars, and pass a qualifying exam, general exam, and dissertation defense. Students must maintain a GPA of 3.25 or higher. Applicants must have a bachelor's degree with a GPA of 3.0 for the final 60 semester credits. The university accepts students with a variety of undergraduate majors, but applicants must meet prerequisites for courses in advanced math, either calculus or higher or statistics; at least two courses in computer programming; and a course in biology or zoology. GRE scores are preferred, but the college will accept GMAT, MCAT, or DAT scores. Cohorts enter in the fall.
University of Wisconsin-Milwaukee
Students in the Ph.D. in Biomedical and Health Informatics program at the University of Wisconsin Milwaukee choose from six specialty concentration tracks: translational bioinformatics, knowledge-based systems, health services management and policy, health information systems, medical imaging and instrumentation, or public health informatics. The curriculum requires students to complete 58 to 63 credits, and up to 24 credits from a related master's program can be applied. Students take 13 to 15 core credits, 33 to 36 credits in the concentration, and complete a dissertation. Applicants should have a master's degree in biomedical and health informatics or a related field, such as health science, nursing, computer science, electrical engineering, or business administration. Well-qualified students with a bachelor's may apply. Applicants must submit GRE scores and two recommendations.
Vanderbilt University has a Ph.D. in Biomedical Informatics that is designed for students who want to be involved in research. Students who earn the degree typically have a background in medicine or computing and go into a career in academic research or research for industry. Ph.D. students take five core courses in bioinformatics and at least three courses each in three areas of competency: computer science and informatics, biological and health sciences, and research methods. Ph.D. candidates must complete a master's degree first, complete 72 credits, pass a comprehensive exam, and produce a dissertation. Applicants should have at least a bachelor's degree in a technical field such as a life science, health-related field, or computer science. GRE scores are required. Students enter in the fall.
Worcester Polytechnic Institute
Worcester Polytechnic Institute offers a Ph.D. in Data Science that is interdisciplinary, incorporating content from the departments of computer science, math, and business. Students are required to take coursework in five areas, including integrative data science, mathematical analytics, data management, data analytics, and business intelligence. Students must also complete directed research and dissertation research. The curriculum requires 60 credits beyond the master's degree, and accepted students who do not have one must complete a Master of Science in Data Science first. Applicants must have at least a bachelor's degree. GMAT or GRE scores are not officially required for domestic students, but the college recommends all applicants submit them. Students may enter the program in the fall or spring.