Genomic Medicine with Data Science

  • //applyindex.com/wp-content/uploads/2023/11/United-Kingdome.png UK
  • University/Institute Name University of Leeds
  • Attendance Type Online (Part Time)
  • Position Duration2 years
  • Application deadlineFeb 2026

Position Details (Master's)

Informed by industry experts and designed by University of Leeds leading academics, this online Masters in Genomic Medicine with Data Science has been developed to upskill and support your career progression.

There is a growing demand across the pharmaceutical, life and health sciences for skilled graduates with both biological knowledge and the computational and analytical interest to drive genomic precision medicine. From early diagnosis, to drugs based on our unique genetic codes, to disease prevention, this course aims to equip you with the skills needed to make a real-world impact.

Aimed at both professionals and graduates with a biological or medical background, you will gain the skills to use large volumes of complex data, encompassing genomics, proteomics, metabolomics, phenotypic data, epidemiology and clinical trial investigations, to improve the understanding of disease mechanisms. This will include the use of bioinformatic tools and statistical principles and methods that are foundational to artificial intelligence.

Career opportunities

As outlined in the recent publication ‘Science Industry Partnership: Skills Strategy 2025’, there is a demand amongst employers for the skills that you will develop on this program.

Upon completion of thisMasters in Genomic Medicine with Data Science from University of Leeds you’ll be well-placed to progress or enter roles in the NHS or industry such as:

  • Computational biology
  • Data analytics functions
  • Clinical genetics
  • Bioinformatician
  • Clinical scientist
  • Clinical leadership in genomic medicine
  • Data validation coordinator
  • Public health intelligence analyst.

Courses included:

  • Programming for Data Science
  • High-Throughput Technologies
  • Statistical Methods
  • Data Science
  • Genetic Epidemiology

Research Areas & Fields of Study involved in the position

Position Start Date

Mar 2026