Precision Medicine: Genomic Data Science MSc

Year of entry

Postgraduate Virtual Open Day

Wednesday 15 February Find out more

Start date
September 2023
Delivery type
On campus
Duration
12 months full time
Entry requirements
A bachelor degree with a 2:1 (hons)
Full entry requirements
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any single component
UK fees
£13,250
International fees
£28,000

Course overview

The silhouette of a man standing in front of a large screen. On the screen is an image of a tumour in pink and white.

Transform healthcare through personalised genomic medicine

The rapid transformation of healthcare through personalised genomic medicine is matched only by the consistently growing demand for talented graduates with the right skill-set.

From early diagnosis, to drugs based on our unique genetic codes, to disease prevention, there is a huge demand for more biomedical scientists with analytical skills. Responding to this gap, this unique course has been designed to directly meet the need for those with both biological knowledge and the computational and analytical interest to drive genomic precision medicine.

Whether you’re experienced with data analysis or not, this course will develop your skills and provide extra support for those students who are less confident in their mathematical ability.

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.

Upon completion, you will find you have an excellent chance of moving into the analytical genomics field in industry, the NHS and academia.

Course highlights

Course details

Course Content

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 including:

  • High throughput sequencing, proteomics and metabolomics

  • Genome-wide genotyping, bioinformatic and gene expression data.

  • Regression, classification and random forests

  • Highly interdisciplinary learning and teaching

You'll have access to the very best learning resources and academic support during your studies. The programme is highly interdisciplinary and combines academic expertise across three faculties: Biological Sciences; Medicine and Health; Engineering 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 3-4 month 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 and contribute to our world-leading research. You’ll be supervised by researchers who are active in the field of genomics and data analytics and work within their groups.

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: Genomic Data Science MSc in the course catalogue

Year 1 compulsory modules

Module Name Credits
High-Throughput Technologies 15
Biopharmaceutical Development: Clinical 10
Analytical Skills in Precision Medicine 20
Research Project: Genomics and Analytics 60
Introduction to Genetic Epidemiology 15
Statistical Theory and Methods 15
Statistical Learning 15
Big Data and Rare and Common Disorders 15
Cancer Drug Development 15

Learning and teaching

You will be taught through a mixture of ‘traditional’ lectures, seminars, workshops, and hands-on computing practicals as well as being embedded within a research group for your project with one-to-one supervision.

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

Students are assessed throughout the year both individually and in groups with coursework, such as data analyses, essays, poster presentations and oral presentations as well as written exams.

For your independent advanced research project you choose from a wide list of topics, which are designed to offer you an immersive individual research experience, as well as the opportunity to contribute to science in an area you are passionate about. This is then assessed as a written dissertation and an oral presentation.

Applying

Entry requirements

Applicants should normally have a bachelor’s degree with at least a 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 requirements

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


Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks)

We also offer online pre-sessionals alongside our on-campus pre-sessionals. You could study a part-time online course starting in January, or a full-time course in summer. Find out more about online pre-sessionals.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

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.

Find out more about how to apply

The link at the top of this page takes you to information on applying for taught programmes and to the University's online application system.

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.

Taught postgraduate confirmation

Taught postgraduate applicants are required to submit their results for consideration as soon as possible. Applicants who require a Student visa to study in the UK are recommended to submit their results no later than 31 July, although they will still be considered if submitted after this date.

Interviews

It is standard procedure to interview applicants, prior to making a decision on their application, for MRes Neuroscience, MSc Biopharmaceutical Development (Industrial) and MSc Sport and Exercise Medicine. Interviews do not form part of the standard admissions process for other programmes in the Faculty of Biological Sciences.

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

University of Leeds Taught Admissions Policy 2023

This course is taught by

Faculty of Biological Sciences

Contact us

Faculty of Biological Sciences postgraduate taught admissions team

Email: fbspgt@leeds.ac.uk
Telephone: +44 (0)113 343 1418

Fees

UK: £13,250 (per year)

International: £28,000 (per year)

Read more about paying fees and charges.

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.

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 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

Recent graduates from the course have gone on to PhDs, and to work in data analytical roles in the NHS, in academia and in the biopharmaceutical industry.

At our annual industry awareness day we invite guests from the NHS and pharmaceutical industry to talk about the research they do and the career opportunities available. Students can chat to them privately for careers advice.

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.

Student profile: Diogo Ann Onuselogu

I now have a better understanding of how various aspects of computer science and biology/medicine can co-operate to reveal great insights about health and disease. The breadth of application is simpl
Find out more about Diogo Ann Onuselogu's time at Leeds