Genomic Medicine with Data Science (online) MSc

Course overview

Join the next generation of genomic medicine pioneers with a focus on data science

Informed by industry experts and designed by leading academics at Leeds, this online MSc in Genomic Medicine with Data Science is tailored to upskill and advance your career. With a growing demand across the pharmaceutical, life and health sciences for specialists in genomic and precision medicine, genomic data analysis and health data analytics, this programme equips you with the skills needed to make a real-world impact in the evolving field of precision medicine.

Who is this course for?

This MSc in Genomic Medicine with Data Science is designed for professionals and graduates with a background in biological sciences, genetics or medicine. Those from a data science background should also have prior knowledge of genetics or molecular biology. You will gain the skills to use large complex datasets, including genomics, proteomics, metabolomics, phenotypic data, epidemiology and clinical trial data. Learn how to drive understanding of disease prevention, early diagnosis and precision treatment through ‘omics-based approaches', which are integral to the use of AI in genomic data science.

Accessible from anywhere in the world, this flexible online course allows you to study at your own pace, fitting around your professional, family and personal commitments.

You will gain hands-on experience working with real-world high-throughput technologies, from next generation sequencing to single cell analysis, enhancing your data science design skills.

Learn from expert researchers and explore how big data is revolutionising medical research and practice. You will focus on the latest developments in both complex and rare diseases, from precision diagnostics to anti-cancer drug development, to improve patient outcomes.

You will learn to use specialised computational tools to analyse genomic, proteomic and other high throughput data, and better understand their function and impact on disease.

By the end of this part-time online MSc, you will have the necessary skills to advance your career in roles such as a Clinical Data Analyst, Bioinformatician, Pharmaceutical Data Consultant, Bioinformatics Analyst and scientist, Statistical Programmer, or Research Assistant.

Graduates of this programme will be able to shape the future of genomic and precision medicine, making a tangible impact in industry and research.

Course highlights

• Gain a Masters in Genomic Medicine with Data Science from a World Top 100 University (QS World Rankings 2026)
• Learn from expert academics from Molecular and Cellular Biology, Medicine, Mathematics and Computer Science.
• Develop expertise in high-throughput technologies, including genomic data analysis and next-generation sequencing.
• Benefit from the programme’s development consultation with industry leaders such as GSK, AstraZeneca, and LabCorp as well as key healthcare organisations like the NHS. This ensures it aligns closely with industry needs.
• The University of Leeds is a partner of The Alan Turing Institute, the UK’s prestigious national institute for data science. The partnership is spearheaded by the Leeds Institute for Data Analytics (LIDA).

This MSc provides you with the data science degree online you need to unlock new opportunities in the rapidly expanding field of genomic medicine.

Join our upcoming webinar

Interested in genomic medicine? Join our webinar to explore the course, understand the learning experience, and hear from our academics and admissions team.

You’ll also have the opportunity to ask questions during the session.

• Date: 21 May
• Time: 16:00

→ Register your place

Revolutionise medicine online: MSc in Genomic Medicine with Data Science

Video transcript

Audio described version of the video

Course details and modules

Our online MSc Genomic Medicine with Data Science is designed for professionals looking to advance their expertise in genomic data analysis, precision medicine, and health data analytics while balancing a career and personal commitments.

Course Structure

The course begins with a two-week online induction, preparing you for online learning at the University of Leeds. It will introduce the study skills you will need to successfully complete your degree.

Following this, you’ll complete ten 15-credit specialist modules and a final 30-credit extended data analysis module, covering cutting-edge topics in genomic medicine.

You’ll typically spend eight weeks per module, with the modules grouped into three carousels, allowing you to take the modules within each carousel in any order. You will usually complete all of the modules in the Foundation Carousel before progressing to the Development Carousel and then the Advanced Carousel.

Foundation carousel

Programming for Data Science (15 credits)

Build a firm foundation in programming for data analysis and AI systems, recognising a diversity of backgrounds. If you have prior programming experience (e.g. computer scientists), you will be fully-stretched here, with material to extend your programming and system-building knowledge through self-learning supported by on-line courseware.

High-Throughput Technologies (15 credits)

Gain an understanding of the use of high-throughput biomolecular data generation methods. The emphasis will be on understanding methods and the data that they typically give. Techniques covered will include whole genome/exome sequencing, gene expression, RNA-seq and epigenetics, proteomics, chemical proteomics, high-throughput RNA biology, single-cell methods and metabolomics.

Statistical Methods (15 credits)

This comprehensive introduction to statistical thinking and data analysis including probability rules and distributions, methods of estimation and hypotheses testing and present the basics of Bayesian inference.

Development carousel

Data Science (15 credits)

Understand methods of analysis that allow you to gain insights from complex data. Cover the theoretical basis of a variety of approaches, placed into a practical context using different application domains.

Analytical Skills in Precision Medicine (15 credits)

Learn how to evaluate and use DNA and protein sequences and structure. The emphasis will be on the use of computational tools to gain information about genes and variants, their function and associations with disease, as well as predicting protein structure.

Genetic Epidemiology (15 credits)

Take an introduction to genetic epidemiology covering the main topics of current interest in the field. An introduction to human genetics will be included, but the main emphasis is on understanding statistical and epidemiological aspects of the study of the genetic basis of human diseases.

Clinical Trials (15 credits)

Understand the principles of clinical trial design, conduct, analysis and reporting. The emphasis will be on understanding the practical issues that arise through real examples backed up with the relevant theory. It will provide a grounding in the basic specialist knowledge and skills required by a non-statistician working on phase II/III clinical trials.

Big Data: Rare and Common Disorders (15 credits)

Gain insight into the way big data is impacting our understanding of human disease and the development of therapies. It will focus on a variety of disorders ranging from rare Mendelian disease to common disorders of complex aetiology. You will gain a thorough understanding of the exciting way big data is influencing medical research and practice today, and what opportunities it offers for the future, but they will also have an appreciation of the problems and limitations that it brings.

Statistical Learning (15 credits)

Understand how statistical learning is at the core of the modern world, translating data into knowledge. Online advertising, automated vehicles, stock market trading, transport planning all use statistical models to learn from past data and make decisions about the future. Statistical learning is a way to rigorously identify patterns in data and to make quantitative predictions.

Advanced carousel

Cancer drug development (15 credits)

Focus on the challenges and latest developments in anti-cancer drug development from a pharmacological point of view. The aim is to provide a good understanding of the processes and difficulties in successfully translating anti-cancer research into clinical practice to improve patient outcomes.

Extended Data Analysis Topics (30 credits)

In this final module, you will apply your data science and health informatics skills to real-world genomic datasets provided by researchers at Leeds, gaining hands-on experience in clinical trials, population health, and precision medicine.

By the end of the programme, you will be equipped with the specialist knowledge and practical skills to pursue a career in genomic medicine, bioinformatics, data science, and health data analytics.

For more information and a full list of typical modules available on this course, please read Genomic Medicine with Data Science (online) MSc in the course catalogue

Learning and teaching

You’ll be taught by expert academics from across four University of Leeds schools, reflecting the multidisciplinary nature of this programme. The programme is delivered 100% online via our award-winning virtual learning environment, Minerva, allowing you to study flexibly alongside your professional and personal commitment.

You will access a wide range of digital learning resources including:

• Pre-recorded lectures, interactive course readings and practical activities to support your learning.
• Live synchronous seminars for real-time discussions with peers and academics
• Asynchronous activities (e.g. discussion forums) allowing you to engage at your own pace.

This active learning approach ensures that you acquire knowledge and apply it to real-world challenges in genomic science, precision cancer medicine, and population health.

Flexible, Career-Focused Learning

We recognise that people have busy lives, so our fully online MSc enables you to gain an online degree in genomic medicine with data science from a world-leading institution, without the added cost of relocating.

Study planners and progress-tracking tools will support your learning, helping you balance your studies with other commitments.

On this course, you’ll be taught by expert academics—including lecturers, professors, and, in some cases, industry professionals—connecting you to leading expertise in the field.

On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

Assessments provide an opportunity for you to demonstrate the knowledge and skills you have developed in the module. Each 8-week module consists of 6 weeks of teaching, followed by two weeks dedicated to assessments and a short break prior to your next module.

For a 15-credit module, you will typically complete one to two assessments, with formative assessment opportunities integrated throughout the 6-week study period.

Assessment methods may include:

• Programming assignments
• Data analysis assignments
• Written project reports
• Online tests.

During the extended data analysis module, you will conduct in-depth analyses using various methodological approaches on molecular and genomic data.

Applying

Entry requirements

You should meet ONE of the following requirements:

• A 2.1 (hons) bachelor degree or equivalent, in a relevant scientific discipline related to biological or natural sciences.
• A 2.2 (hons) bachelor degree or equivalent, in a relevant scientific discipline related to biological or natural sciences, with a minimum of 2 years’ relevant work experience.
• A 2.2 (hons) degree or equivalent, in any subject with a minimum of 3 years’ relevant experience.

Applications will be individually assessed based on the evidence of educational and work experience provided.

We accept a range of international equivalent admissions qualifications. For further information, please contact our admissions team.

English language requirements

Proficiency in English language is essential to study at the University of Leeds. You will need either:

Alternative English Language Qualification

A degree taught in English from a recognised institution, lasting at least two years at the undergraduate level or one year at the Masters level, which can be evidenced by transcripts and/or certificates.

For more details, contact our Enrolment Advisors at onlineadmissions@leeds.ac.uk

English language requirements

IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.

How to apply

Click the ‘Apply’ button at the top of this page to start your application via the University's online application system. If you want more information first, you can ‘register your interest’.

For assistance with your application, contact onlineadmissions@leeds.ac.uk and our team will be happy to help.

Application deadlines

The deadline for applications to join each intake are outlined below:

• March 2026 start: Apply by 17 February 2026.

As part of the selection process, candidates may be invited for a telephone or online interview.

Identification

The University of Leeds requires all applicants for fully online programmes to provide proof of their identity at the point of application. Accepted forms of ID are:

• passport photo page, or
• driving licence, or
• national identity card.

Admissions policy

University of Leeds Admissions Policy 2026

Contact us

Online Admissions team

Email: onlineadmissions@leeds.ac.uk
Telephone:

Fees

UK: £13,000 (Total)

International: £13,000 (Total)

These fees apply to those starting their course between September 2025 and July 2026.

The fee is composed of (which can be paid on a module-by-module basis*):

• ten taught modules (15 credits each): £1,100 per module
• project module fee (30 credits): £2,000

* If you are receiving a student loan or your fees are being paid directly to the University by your employer or sponsor you will not be able to pay on a module-by-module basis. Please check with the Admissions Team.

Read more about paying for online courses.

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

Scholarships are also available to help fund your Masters. Find out more and check your eligibility below: 

• Scholarships for International students 
• Scholarships and funding for UK students
• Your subject area may also offer scholarships

Career opportunities

According to the ‘Science Industry Partnership: Skills Strategy 2025’, employers are increasingly seeking the skills that you will develop on this programme.

Upon completion, you’ll be well-placed for roles in the NHS and industry such as:

• Computational biologist
• Data analyst
• Clinical geneticist
• Clinical scientist
• Bioinformatician
• Clinical leadership in genomic medicine
• Data validation coordinator
• Public health intelligence analyst.

Careers support

The University of Leeds Careers Service offers extensive online resources to help you maximise your studies and achieve your career goals:

• One-to-one support from a careers advisor via telephone or virtual meeting
• Online career workshops, webinars and resources
• A database of job opportunities and online employer events
• LinkedIn Learning platform
• CV writing tips and job application support
• Interview coaching and practice sessions.

The Careers Service also connects students seeking to work in a specific region, and offers professional development through alumni network, online support and employer partnerships.