Ph.D Biomedical Data Science

Biomedical Data Science Ph.D. program

Ph.D

Degree Granted

4 year minimum

Length of Program

Fall, Spring, Summer

Term

Online

Format

$37,800

Tuition/Per Year Additional fees apply

Ph.D Biomedical Data Science

Biomedical Data Science Ph.D. program

Ph.D

Degree Granted

4 year minimum

Length of Program

Fall, Spring, Summer

Term

Online

Format

Ph.D

Tuition/Per Year Additional fees apply

Lead with data and improve health care and public health through our Biomedical Data Science Ph.D. program

Through biomedical data science, you can learn to analyze biomedical data to better understand diseases and provide improved – and more affordable — health care. In Meharry’s Biomedical Data Science Ph.D. program you will learn to discover new knowledge from biomedical data sets. You will collaborate with faculty, and conduct independent research, to develop new technologies and novel data analysis methods.

Scholarships

Students are eligible for scholarships. 

Learn more about scholarships.

  • Curriculum
  • Requirements
  • Courses
  • Admission Requirements
  • Contact
  • Career Outlook

We know that pursuing a doctorate program is one of the biggest career decisions you will make. The Biomedical Data Science Ph.D. will prepare you to develop novel tools and leverage real-world, massive biomedical data to advance precision health, drug discovery and other areas of biomedical science.

The curriculum for the Biomedical Data Science Ph.D. program combines mathematics, computational science, biostatistics, biomedical informatics and computer programming. Your program will begin with foundation and core courses that provide a thorough education in biomedical data science. You will then take biomedical data science electives and research seminar courses before beginning your dissertation.

Highlights include:

  • Mathematical and statistical theory
  • Design and analysis of algorithms
  • Advanced scientific computing
  • Distributed algorithms and optimization
  • Advanced biostatistics
  • Big data management and analytics
  • AI and computational ML
  • Computational software engineering
  • Predictive modeling and analytics
  • Visualization and unstructured data analysis
  • Privacy and Security in health care
  • Ethical, Legal and Societal Issues in health care

Graduation Requirements

Completion of the program requires 75 graduate credits. To provide a common background in biomedical data science, twelve core courses are required for all students. In addition to the core courses, students will take at least 6 hours of electives, at least 6 hours of research seminar and 12 hours of dissertation and defense.  

 

12 credit hours of foundational leveling courses:  

  • MSBD 501 Introduction to Bioinformatics 
  • MSBD 502 Computational Structural Biology 
  • MSBD 503 Introduction to Epidemiology  
  • MSBD 710 Mathematical and Statistical Theory 

 

36 credit hours (12 core courses) including the Candidacy Exam:  

  1. MSBD 540 Intro to Artificial Intelligence for Health Care  
  2. MSBD 550 Applied Machine Learning  
  3. MSBD 555 Big Data Management and Analytics  
  4. MSBD 566 Predictive Modeling and Analytics  
  5. MSBD 570 Visualization and Unstructured Data Analytics  
  6. MSBD 720 Advanced Biostatistics  
  7. MSBD 725 Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference and Optimization  
  8. MSBD 726 Biomedical Imagining, Processing and Analysis  
  9. MSBD 735 Advanced Epidemiology for Public Health  
  10. MSBD 736 Ethical, Legal and Societal Issues in Healthcare  
  11. MSBD 740 Privacy and Security in Healthcare  
  12. MSBD 800 Candidacy Exam  

 

9 elective hours from the following courses:  

  • MSDS 560 Natural Language Processing 
  • MSBD 610 Network and graph theory for Biomedical data analytics  
  • MSBD 730 Advanced Deep Learning  
  • MSBD 746 Consultant Workshop on Biomedical Data Science 
  • MSBD 755 Special Topics 

Or courses recommended and approved by the academic/research advisor 

 

6 credit hours of research seminar from the following courses:  

  • MSBD 750 Directed Reading and Research  
  • MSBD 870 Literature Review  
  • MSBD 880 Proposal Manuscript and Defense  

 

12 credit hours of Dissertation and Defense:  

  • MSBD 890 Dissertation and Defense  

Candidacy Exam and Dissertation Committee

Upon admission to the program, each student will work towards completing the courses leading up to passing the Candidacy Exam and gaining candidacy as a Ph.D. student, as this is a major milestone event. During this time, the student may seek academic guidance from the program director.

Student enrollment in MSBD 800 Candidacy Exam shall signify your intent to take the exam.

Upon successful completion of the Candidacy Exam, the candidate may seek formation of a Ph.D. Dissertation Committee, which requires an approval document to be completed by the committee chair, members and student. The committee chair will become your primary resource for advisement and guidance for planning your proposal submission and defense, then subsequent dissertation presentation and defense.

MSDS 510 Computer Programming Foundations for Data Science  

MSDS 520 Mathematical and Statistical Foundations for Data Science  

MSDS 525 Data Management Foundations for Data Science  

MSDS 535 Further Mainstream Programming Languages for Data Science  

MSDS 710 Mathematical and Statistical Theory 

MSDS 550 Computational Machine Learning  

MSDS 555 Big Data Management and Analytics  

MSDS 565 Predictive Modeling and Analytics  

MSDS 570 Visual Analytics  

MSDS 580 Research Methods  

MSDS 700 Fundamentals of Database Management Systems  

MSDS 715 Data Modeling for Big Data  

MSDS 720 Advanced Statistics  

MSDS 725 Adv Scientific Computing: Stochastic Methods for Data Analysis, Inference & Optimization  

MSDS 730 Deep Learning  

MSDS 736 Ethical, Legal & Societal Issues in Healthcare  

MSDS 740 Big Data Privacy and Security 

MSDS 550 Computational Machine Learning  

MSDS 565 Predictive Modeling and Analytics  

MSDS 700 Fundamentals of Database Management Systems  

MSDS 710 Mathematical and Statistical Theory  

MSDS 715 Data Modeling for Big Data  

MSDS 720 Advanced Statistics. The candidacy exam is normally taken at the end of the second year. 

MSDS 750V Individual Studies  

MSDS 870V Literature Review  

MSDS 880V Seminar 

MSDS 560 Natural Language Processing  

MSDS 610 Network and Graph Theory for Data Science  

MSDS 620 Signal Processing for Big Data  

MSDS 655 AI in Cyber Security  

MSDS 727 Digital Image Processing and Understanding 

MSBD 890 Dissertation and Defense

Admission Requirements

Applications for the Data Science Ph.D. program and the Biomedical Data Science Ph.D. program are accepted for the Fall Semester, according to the deadlines below. All admitted candidates will be expected to demonstrate an aptitude for quantitative and computational sciences, which may encompass mathematics, statistics, information systems/technology, fundamental programming skills, and related subjects.

Admission decisions will be based on all aspects of the application, including (1) prior academic performance of the applicant in a baccalaureate or master’s program at a regionally-accredited institution, including coursework and independent research projects, (2) relevant work experience, (3) the applicant’s statement of purpose, (4) letters of support, and test scores.

Fall 2026 application deadline

  • May 31, 2026: application deadline.
  • June 15, 2026: All materials outlined below are due.

Application Process

Only completed applications will be considered. Applicants may check the status of their application by checking their application portal.

Step 1

  • Submit the online Ph.D. application.
  • A separate statement of purpose that establishes (1) the applicant’s preparation for graduate school, (2) reasons for pursing a graduate degree, (3) prior relevant work or research experience, and (4) ultimate career objectives. The statement of purpose should not exceed 1000 words and can be submitted via the application portal

 

Step 2

  • Resume or curriculum vita.
  • Three letters of recommendation from academic or professional sources are required. Among these three letters at least one must be from an academic source. Letters should not come from family members or close personal friends. All letters should:
    (1) describe the recommender’s relationship with the applicant,
    (2) address the applicant’s likelihood to succeed in graduate school, and
    (3) speak to the applicant’s verbal and written communication skills, collegiality, and predisposition for quantitative analysis and investigation.
    Recommenders must submit letters directly to Meharry Medical College.
  • Official transcripts
  • Applicants must submit official transcripts of coursework attempted and completed at all previous colleges and universities whether or not a degree was earned at the institution. Please ask your institution to send official transcripts directly to the Office of Enrollment Management to sacsenrollment@mmc.edu.

If the institution prefers to mail transcripts, please use this address:

Office of Enrollment Management
School of Applied Computational SciencesMeharry Medical College,
3401 West End Avenue
Suite 260
Nashville, TN 37203

All submitted transcripts become the property of the Meharry Medical College and will not be returned.

Required test scores

The GRE, GMAT, or MCAT test score requirement is waived for applicants at this time. We do ask that any applicants submit any previous test scores. All scores must be sent directly to Meharry Medical College, via sacsenrollment@mmc.edu, in electronic form.

Interview

We will invite select applicants who have completed an application via email for a virtual interview with the faculty admission committee. Interviews will be conducted with cameras on and may be recorded for internal use only. Applicants must complete the interview process to be considered for admission. Final admissions decisions will be made from the pool of interviewed applicants.

Acceptance

Applicants will be notified of their admission decision via the applicant portal. Those offered admissions will be asked to communicate their decision.

Admission Requirements

Applications for admission are only accepted for the Fall Term each year. The requirements for admission are:

Prior Degree

All applicants must have the educational equivalent of at least a bachelor’s degree in computer science; information technology/systems; mathematics; statistics; engineering; finance; biomedical, health, or life sciences; or a related discipline from a regionally accredited university in the U.S.

Minimum Prior Coursework

The prior degree(s) must encompass the following minimum coursework requirements, in which applicants must have earned a grade of B or better:

  • Two semesters of college calculus, and one semester of linear algebra.
  • One semester of calculus-based statistics and/or probability at the college level
  • One semester of college-level computer programming fundamentals or one year of demonstrated, verifiable programming experience in a work setting.

 

Biomedical Data Science applicants should also have at least one semester of college-level biology or related coursework in the biological/health/life sciences.

Additional Recommended Prior Coursework and Experience

Additional coursework and/or experience is recommended, as outlined below:

Applicants for Biomedical Data Science Ph.D. program

  • Competency in a second focus area that complements the applicant’s previous degree(s) in one of the preferred fields identified above, as demonstrated by completion of a major, minor, or certificate in one of these areas. For example, applicants whose prior degree(s) are in one of the quantitative fields should ideally possess competency in a biological/biomedical/health sciences field, and applicants whose prior degree(s) is in a biological/biomedical/health sciences field should ideally possess competency in a quantitative field.

 

Applicants for both Ph.D. programs

  • Competency in a second focus area that complements the applicant’s previous degree(s) in one of the preferred fields identified above, as demonstrated by completion of a major, minor, or certificate in one of these areas.
  • More advanced courses in mathematics and statistics, such as multivariable calculus, differential equations, linear programming, mathematical statistics, biostatistics, biomathematics/biophysics, and bioinformatics.
  • More advanced courses in computer science and/or software engineering beyond fundamentals that encompass the ideas of abstraction, modularity, object-oriented programming, data structures, and algorithm design.
  • Evidence of relevant research or work experience, including, but not limited to, demonstrated participation in data science/analytics projects, leadership of data, computing, or information systems/technology groups or teams, and artifacts such as authored research reports and journal publications that demonstrate the applicant’s research aptitude and verbal communication ability.

 

Minimum Grade Point Average (GPA)

  • All applicants possessing a baccalaureate degree only must have earned a minimum cumulative GPA of 3.00 (on a 4-point scale) equivalent of the last 60 semester hours (approximately two years of work).
  • Applicants possessing a master’s degree must have a minimum cumulative GPA of 3.0 (on a 4-point scale).
  • Applicants possessing a baccalaureate degree plus some graduate work, but not a graduate degree, must have a minimum cumulative GPA of 3.0 (on a 4-point scale) individually in both sets of coursework. GPA should be based on scale of 4.0.

 

Other Qualifications

We may also consider other qualifications presented by applicants, such as strong oral, verbal, and interpersonal communication skills, as well as overall goodness-of-fit for the Ph.D. program.

Additional Requirements for International Applicants

International applicants must hold a degree comparable to a regionally accredited US baccalaureate or master’s degree. Applicants submitting transcripts from international colleges and universities are required to have them verified for US degree program equivalency before being considered for admission. Verification from the following organizations is acceptable:

  • International Education Services (IES)
  • World Education Services (WES)
  • Global Credential Evaluators (GCE)
  • Educational Credential Evaluators (ECE)

The decision of the verifying organization must be transmitted directly to Meharry Medical College in electronic form.

English proficiency

Adequate proficiency of spoken and written English is essential to success in graduate study, and medical residency training at Meharry Medical College.

Please review Meharry’s  F-1 English Language Policy and the College’s English proficiency requirements policy.

Transfer Students

Applicants who are enrolled in a Ph.D. program in biomedical data science or related field outside Meharry Medical College may apply for Meharry’s BDS Ph.D. program as a transfer student. Transfer students are subject to the admissions requirements stated above; and therefore, the transfer track is only recommended for first- or second-year graduate students. Applicants transferring from another institution and who are in good standing at that institution are exempt from the graduate admission exam and TOEFL requirements. A recommendation letter from the previous advisor or program director is required. A maximum of six (6) credit hours can be transferred. For more information, please contact The Office of Enrollment Management at sacsenrollment@mmc.edu.

** Please redact sensitive information prior to sending FERPA protected data via email or contact us for other security options.

JeanLuc Nshimiyimana, M.Ed
Director, Enrollment Management & Professional Development

sacsadmissions@mmc.edu

Biomedical data science career outlook

Biomedical data scientists also enjoy rewarding salaries*.

Average salary 2024

$123,544

*According to Glassdoor, June 2024.