Precision Medicine: Genomics & Analytics MSc

Interdisciplinary training in biomedical data analysis

Biomedical research generates large volumes of complex data, encompassing: genomics, proteomics, metabolomics, phenotypic data, epidemiology and clinical trial investigations, to inform our understanding of disease mechanisms.

This course will equip you with the skills to utilise these data sets in the development of precision medicine. Data impacts on the creation of new tailored therapies, aiding earlier diagnosis and the selection of optimal treatment regimens for patients who may be suffering from disorders ranging from common disorders of complex aetiology (such as cancer or cardiovascular disease) to the more rare Mendelian disease (such as muscular dystrophy).

This distinctive course has been designed to directly meet research needs in industry and academia where there’s a need for scientists with both biological knowledge and the computational, statistical and analytical skills to drive genomic precision medicine.

Pioneering data science research at Leeds

The University of Leeds is now 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) with contributions from researchers and data scientists across the University. Research in LIDA sheds new light on health and human behaviour and the action needed to tackle a wide range of medical, social and environmental problems.

You’ll benefit from a research-led education at the forefront of the most innovative data analytics research at Leeds.

LIDA is supported by national programmes such as the MRC’s Medical Bioinformatics who invested £5.7 million to enable ground-breaking and productive bioinformatics research at the interface between the clinic, health records and high volume molecular and phenotypic data sets.

Leeds has also recently been the recipient of huge investments from funding councils across the UK, such as the recent £10 million investment in artificial intelligence and digital pathology.

This degree will prepare you for the rapidly expanding and developing field of precision medicine, equipping you with the diverse skill set needed to work in this data-centric discipline.

The modules on this course will introduce you to the advanced technologies used to generate large scale genomics data and the variety of statistical and computational methods used to analyse:

• high throughput sequencing, proteomics and metabolomics

• regression, classification and random forests

• genome-wide genotyping and bioinformatics.

Highly interdisciplinary learning and teaching

You'll have access to the very best learning resources and academic support during your studies. We’ve been awarded a Gold rating in the Teaching Excellence Framework (TEF, 2017), demonstrating our commitment to delivering consistently outstanding teaching, learning and outcomes for our students.

The programme is highly interdisciplinary and combines academic expertise across three faculties: Biological Sciences, Medicine and Health, Maths and Physical Sciences. You’ll be able to work with real-life data sets generated through our own research.

Some of your lectures will be delivered by external speakers from industry and the NHS who will use case studies to illustrate different approaches to using data analytics in precision medicine. You’ll also receive a solid grounding in a range of transferable skills, valued by employers, including: teamwork, project work, and knowledge of the legal, ethical and professional guidelines that are relevant to research data use.

Our cancer biology module is delivered at St James’s University Hospital campus site which is home to many cancer researchers located in the Wellcome Trust Brenner Building and the Clinical Sciences Building.

Research Project

You’ll complete a 60 credit research (computational) project where you will gain in-depth experience of the analysis of large-scale biomedical data to address problems related to health and disease. You’ll be supervised by researchers who are active in the field of genomics and data analytics.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

For more information and a full list of typical modules available on this course, please read Precision Medicine: Genomics & Analytics MSc in the course catalogue

Modules

Year 1

Learning and teaching

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.

Entry requirements

BSc First Class or 2:1 or equivalent in a relevant scientific discipline which would normally be one of the biological sciences or natural sciences. Subject to University regulations, MBChB or BDS students who had completed 3 years of study would be eligible to intercalate.

While the course does not assume any prior knowledge of statistics, we require that students demonstrate their aptitude for statistics from either undergraduate teaching in statistics/mathematics, an A-level (or equivalent) in mathematics or other relevant experience.

English language requirement: IELTS 6.5 overall, with no less than 6.0 in any single component. Alternative English language requirements that are acceptable are:

• TOEFL (Test of English as a Foreign Language) of 92 overall, with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing.

• Pearson (Academic) of 64 overall with no less than 60 in any component.

• Cambridge Advanced English (CAE) of 176 overall with no less than 169 in any component.

• Trinity College Integrated Skills in English of a Pass in ISE II or above (if taken in the UK).

English language requirements

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

How to apply

Documents and information you’ll need:

• completed online application form (for Taught Postgraduate Study)

• full CV

• transcript of degree examination marks achieved to date

• copy of final degree certificate (if completed)

• evidence of English language qualification (non-native English speakers only)

• copy of passport (if you’re an overseas student)

• completed supporting statement.

To help us assess your application, please write a supporting statement. As a guideline, we would expect this statement to be 1-2 pages in length. In your statement please:

• Provide a brief synopsis of any courses/modules you have studied that have covered statistics and/or statistical analysis. Please make reference to your academic transcript, as this information is not always apparent from the course titles.

• Provide details of any previous or current research experience (e.g. undergraduate project, vacation placements, fieldwork, internships). Describe clearly the aim of the work, your part in it, how long the project lasted and whether this research was carried out individually or in a group. Also mention the specific techniques you have used. Again, please ensure that you make reference to the statistical aspects.

• Outline the reasons why you wish to study this particular Masters programme. Explain how the skills and experiences you have outlined above are relevant to your programme of choice and the career you intend to pursue.

For 2020/21 academic year courses the link visible above will take you to information on applying for taught programmes and to the University's online application system.

For courses starting from September 2021, applications will open on October 1st 2020 and you will be able to access the application system from that date.

If you're unsure about the application process, contact the admissions team for help.

Next steps

• we process your application

• we inform you of our decision

• if we make you an offer, you respond by accepting, declining or deferring.

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

Faculty of Biological Sciences Taught Admissions Policy 2021

Fees

• UK: £11,750 (total)
• International: £24,750 (total)

Read more about paying fees and charges.

Brexit 
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.

For fees information for international taught postgraduate students, read Masters fees.

Part-time fees
Fees for part-time courses are normally calculated based on the number of credits you study in a year compared to the equivalent full-time course. For example, if you study half the course credits in a year, you will pay half the full-time course fees for that year.

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 about additional costs

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 for Faculty of Biological Sciences students

We award a generous range of scholarships to UK and international students. We consider all eligible applicants who demonstrate outstanding academic achievement and excellent personal and professional skills. Find out more about the range of scholarships we have to offer.

Government-backed loan up to £11,222. Find out more.

Alumni bursary - If you are a former student of the University of Leeds you may be eligible for a 10% alumni tuition fee bursary

You can also search our postgraduate scholarships database or you can also find information on MoneySavingExpert

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

Upon completion of this programme you’ll be well-placed to undertake a PhD in this field. You may also be able to enter into a number of roles within the industry or NHS:

• Computational biology

• Data analytics functions

• Clinical genetics

• Disease Biologist

• Clinical Scientist

• Clinical leadership in genomic medicine.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.