Health Data Science (MS)

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Degree Offered: MS
Program Leadership:
John Kornak, PhD, Program Director
Thomas Hoffmann, PhD, MA, Associate Program Director
Admissions Inquiries:
Eva Wong-Moy, Graduate Affairs Manager

Program Description

Data science plays a fundamental role in health sciences research: Learning from data is at the core of how we make advances in health research. Data science methods and tools are needed to deal with the expanding role of precision medicine, the widespread analyses of electronic health records, and the growing number of large and complex datasets. 

The Master of Science (MS) Degree in Health Data Science (MiHDaS) is a two-year program in which students learn to apply data science, biostatistics, machine learning, and epidemiological thinking in clinical research settings.

The program is intended for:

  • Quantitative science learners interested in studying data science with a focus on biomedical applications.
  • Numerically able biomedical scientists interested in applying data science methods in clinical, epidemiological and biological sciences.

We also offer a one-year certificate program (CiHDaS), with condensed coursework and absent teaching and hands on capstone project experience, best suited for those already working in the biomedical or pharmaceutical industries.

Admission Requirements

  • Bachelor’s degree (BA/BS) or the equivalent from an accredited institution in a quantitative or biomedical science, or related field, with a minimum grade point average of 3.0.
  • In addition to meeting the same admission requirements domestic students must meet, international applicants must also demonstrate proficiency in English. There are two ways to meet this English language proficiency requirement, which are outlined on the Graduate Division’s International Admission Requirements webpage. Please note that the Health Data Science program minimum internet based TOEFT iBT score is 100.
  • Transcripts
  • Three letters of recommendation
  • Resume or curriculum vitae
  • Statement of Purpose
  • Personal History Statement

Learning Outcomes

To complete the program, scholars must satisfy program objectives, which are to:

  • Acquire a mastery of a broad set of data science research methods and in the techniques needed for the application of data science across biomedicine applications and research.
  • Gain understanding of key issues that are particularly pertinent to the health sciences and evidence-based medicine, such as bias, confounding, interpretability, and causality.
  • Plan and implement one or more health-related data science research projects.
  • Write and prepare a publication-quality research paper and/or a detailed technological methodology report.
  • Present research results at a scientific meeting or conference.
  • Create a portfolio of data science skills and application areas.