Why study MSc Genomic Medicine (Data Science) at Exeter?
Genomic medicine is revolutionising the future of healthcare, allowing for faster, more accurate diagnosis and effective treatments.
With increasing demand for skilled professionals in this field, our programme equips you with essential biological expertise alongside sought-after data science skills, empowering you to drive transformative progress in genomic medicine.
You will be taught by world-leading academics in genomics research and health data science, including multifactorial traits and pharmacogenomics, and learn how genomics data is analysed and applied in clinical medicine.
Benefit from our flexible study options – study full or part time, with a variety of optional modules to complement your career needs.
Studying MSc Genomic Medicine at the University of Exeter Medical School.
Top 10 in the UK for our world-leading and internationally excellent Clinical Medicine research
Based on 4* + 3* research in REF 2021
Our Public Health research is 11th in the UK for research power
Submitted to UoA2 Public Health, Health Services and Primary Care. REF 2021
Learn from world-leading experts in genomics
Major capital investment in new buildings and state-of-the-art facilities
Entry requirements
Standard entry
Normally a min 2:2 Honours degree (or equivalent) in a relevant discipline. Relevant clinical or professional experience may be taken into consideration as evidence of equivalency. A personal statement, detailing your reasons for seeking to undertake this subject, will be required.
The University is committed to an equal opportunities policy with respect to gender, age, race, sexual orientation and/or disability when dealing with applications. It is also committed to widening access to higher education to students from a diverse range of backgrounds and experience.
International students
Please visit our international equivalency pages to enable you to see if your existing academic qualifications meet our entry requirements.
International students are normally subject to visa regulations which prevent part-time study. It is recommended that international students apply for the level of the final award you intend to complete i.e. PGCert, PGDip or Masters, due to the associated cost and requirements for a Tier 4 student Visa.
Accreditation of prior learning for Masters courses in Healthcare and Medicine
Accreditation of Prior Learning (APL) is a process whereby students, who have already gained relevant skills and knowledge prior to the start of their course, may be granted a partial credit exemption from their programme instead of unnecessarily repeating work.
Genomic medicine is no longer a distant vision but a tangible reality, with the NHS aiming to integrate genomic sequencing into routine care. At the University of Exeter, we're deeply invested in genomics with world-leading research and expertise in cutting-edge technologies.
Our MSc Genomic Medicine (Data Science) pathway is tailored to equip you with both biological knowledge and essential data science skills. As data science becomes increasingly vital in healthcare, this programme positions you uniquely in the job market, ready to lead the charge in advancing genomic precision medicine.
Awards
This MSc course can be studied on a full-time basis over one year or over two or three years (part time), which may suit applicants who are already working full time. The programme is divided into units of study called ‘modules’ which are assigned a number of ‘credits’.
To gain a Masters qualification, you will need to complete 180 credits at level seven. The credit rating of a module is proportional to the total workload, with one credit being nominally equivalent to 10 hours of work, a 15-credit module being equivalent to 150 hours of work and a full Masters degree being equivalent to approximately 1,800 hours of work.
It is also possible to exit with a PGCert after completing 60 credits of taught modules or a PGDip after completing 120 credits of taught modules. The list of modules below shows which are compulsory.
Please note: this timetable is a draft and subject to change
The last contact day and assessment deadline for the programme will be earlier than the actual end date of your registration with the University, to allow a period of time at the end of your active studies for further support and mitigation, if needed.
The modules below provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.
Please note that the module information displayed here is subject to change.
The full MSc course comprises 180 credits made up from seven core modules: six taught modules of 15 credits each and one research module of either 60 or 30 credits. A range of optional modules is available for you to design your own learning experience to complement your career needs, and to complete the full 180 credits required.
It is also possible to exit with a PGCert after completing 60 credits of taught modules or a PGDip after completing 120 credits of taught modules.
135-150 credits of compulsory modules, 30-45 credits of optional modules (subject to choosing 180 credits in total). You must select modules as follows:
Compulsory choice group 2 - select 30-45 credits from this group.
Optional group 1 - select 30-45 credits from this group.
Modules HPDM045, HPDM171, HPDM172 and HPDM182 require on-campus attendance. The other modules can be taken as on-campus modules or online (z-coded modules). HPDM046 will run subject to sufficient interest.
Compulsory modules
Code
Module
Credits
Compulsory 1
Omics Techniques and Their Application to Genomic Medicine
15
Bioinformatics, Interpretation and Data Quality Assurance in Genome Analysis
15
Research Project - Data
60
Fundamentals in Human Genetics and Genomics
15
Compulsory Choice Group 2
Coding in Python for Health and Life Sciences
15
Computational Skills for Health and Life Sciences
15
Statistics for Health and Life Sciences
15
HPDM036: Omics Techniques and Their Application to Genomic Medicine
This module explores state-of-the-art genomic technologies used for DNA sequencing, including targeted approaches, whole exome sequencing and whole genome sequencing, together with RNA sequencing and other technologies used to investigate genomic variation in clinical settings. You will gain an understanding of the principles and applications of these highly parallel sequencing technologies and array-based methodologies used in genomic medicine. The module introduces key bioinformatics approaches for the analysis and interpretation of genomic data. Together with the Introduction to Human Genetics and Genomics module, this module provides a foundation for the subsequent Bioinformatics, Interpretation, Statistics and Data Quality Assurance module. In addition, the module introduces the application of RNA sequencing and other molecular approaches to estimate gene and protein expression, including the study of mRNA, microRNAs and long non-coding RNAs. The module also provides a comprehensive introduction to epigenomics, proteomics and metabolomics, highlighting their roles in the functional interpretation of genomic data and the discovery of disease biomarkers. Applications of omics approaches in areas such as cancer genomics and infectious disease research will be explored to illustrate how integrated genomic data can inform disease mechanisms, diagnostics and personalised medicine.
HPDM041: Bioinformatics, Interpretation and Data Quality Assurance in Genome Analysis
One of the key challenges in genomic medicine is to interpret large-scale sequencing data effectively in order to arrive at an accurate genetic diagnosis. The aim of this module is to provide you with an in-depth understanding of how this process is conducted. You will learn how large-scale genomic data is analysed and interpreted, as well as develop a practical understanding of how bioinformatic and statistical tools are used.
The module will cover the fundamental principles of bioinformatics and data quality assessment as applied to clinical genomics. You will use a range of software packages and in silico prediction tools, alongside genomic and clinical databases. You will learn how to apply these tools to evaluate the quality of a sequencing data set, align sequencing reads to a reference genome, identify genetic variants, and filter variants with evidence of pathogenicity. Theoretical sessions will be coupled with practical workshops and self-paced assignments, where you will get to perform a range of data bioinformatic analyses on real-world data.
By the end of the module, you will be able to use bioinformatic tools to critically interpret real-world data and to accurately report your findings in a diagnostic context.
In this module you will apply and extend your existing knowledge and skills by undertaking an independent research project aligned with your degree programme (MSc Neuroscience, Health Data Science or Genomic Medicine). Projects are selected from a diverse portfolio designed to reflect a wide range of scientific interests and programme specialities. Depending on your programme, projects may involve laboratory-based research, a systematic review, or in silico approaches such as data analysis, computer modelling or bioinformatics. Projects are undertaken within Exeter’s leading research groups and may include collaboration with partners including the National Health Service, pharmaceutical companies and health data organisations.
HPDM082A: Fundamentals in Human Genetics and Genomics
This module will start by covering the fundamentals of nucleic acid structure and function, including changes during the cell cycle. Following this, you will learn the fundamentals of gene expression and its relationship to the architecture of genes and the genome. Next, you will be introduced to the fundamentals of genomic variation, including the various ways it can be classified and its frequency. Lastly, you will apply what you have learnt to interpret genotype and/or phenotype information for the prediction of disease risk, presentation and/or mechanisms.
This module aims to give you a fundamental understanding of DNA structure, function, and variation and recognise its importance to human health and disease. It will prepare you for further modules in genomic medicine that enable a deeper exploration of how genomic information can be used to improve healthcare, medicine, and our biological understanding of human diseases.
HPDM171: Coding in Python for Health and Life Sciences
Modern health research is becoming increasingly focused on the analysis of large, complex datasets. To extract meaningful information from such datasets, health data scientists often use computer programming languages to create bespoke analysis pipelines. Python is the most popular programming language for this task, making it a widely transferrable and employable skill.
This module assumes no prior knowledge of Python or any other computer coding language. We will be teaching Python from the ground up, starting with basic structures and objects available within Python, then developing more complex routines. When the fundamentals are established, you will learn how to manage and visualise data in Python. At the end of the course, you will learn how to perform machine learning tasks in Python, and come out of the module with general transferable computing and code-writing skills that will help you learn new languages quicker.
The overall aim of this module is to introduce students from a non-computing background to computer programming in Python, a common language for health data science. You will learn practical coding skills focused on developing the necessary skills to analyse data.
HPDM172: Computational Skills for Health and Life Sciences
Health data science is a complex field requiring a wide range of computing skills. For example, increasingly, many health datasets are hosted on cloud computing resources and requiring specialist software and multidisciplinary teams to access them. This module complements the Introduction to Python for Health Data Scientists module, with the aim of broadening the scope of the tools available to you as a data scientist. By the end of the module, you will have learned the following skills:
Cloud computing using the Openstack system
Computational thinking, including how to design an algorithm and planning programming using pseudocode
Navigating the Linux command line
Querying relational databases using SQL
Ethical and effective use of generative AI
The benefits of and how to use Git and GitHub for collaborative coding and version control
This module requires no previous knowledge of any of the required skills, although general computer skills will be beneficial.
The aim of this module is to provide a solid foundation in basic computational thinking and provide essential skills in widely used operating systems and computer software.
This module provides a broad introduction to statistical analysis for health and life science applications. The module starts by considering the different stages of a statistical investigation and emphasising the importance of problem formulation. The module highlights the benefits of exploratory data analysis based on descriptive statistics and graphs. Key concepts in probability theory and the role of statistical distributions in modelling health data will be covered. The core part of the module provides a foundation in regression modelling to include simple linear regression, logistic regression, survival analysis and models that account for complex temporal and hierarchical data structures. Embedded through the module is a strong emphasis on the critical evaluation of statistical methodology and interpretation of analysis results in the context of the specific health application. Throughout this module, you will gain practical experience of statistical computing using the R software environment and exposure to case studies based on real-world health data.
Molecular Pathology of Cancer and Application in Cancer Diagnosis, Screening and Treatment
15
Pharmacogenomics and Stratified Healthcare
15
Ethical, Legal and Social Issues in Applied Genomics
15
Counselling Skills for Genomics
15
Advanced Bioinformatics
15
Epigenetics
15
BIOM567: Application of Genomics in Infectious Disease
This module provides an exciting learning opportunity at the forefront of modern biology. You will explore the genomics of infectious agents, including the implications of gain/loss of genes and plasmids upon the pathogenicity and the sensitivity to drug treatment.
You will explore some of the huge range of freely available sequence data and computational tools that underpin modern genomics research.
This module is primarily aimed at clinical practitioners, diagnostic service providers, scientists, researchers and those aspiring to specialise within an academic career pathway. You will learn from, with and about your peers, developing a mutual understanding and respect for the positive contributions that each will bring to Genomic Medicine.
Computer-based practical workshops will consolidate the use of bioinformatics tools and databases through hands-on analysis of genomics data (e.g. comparative genomics of pathogen genome sequences or prediction of antimicrobial resistance).
Key employability skills include extracting and analysing complex information from web-based resources, and awareness of data-driven decision making. You will develop skills relevant to careers in medicine, medical research, and biosciences more broadly.
HPDM037: Genomics of Common and Rare Inherited Diseases
This module is available either via blended learning with contact days on-campus supported by online learning, or as fully distance learning via our online platform.
This module explores the genetic basis of common and rare inherited disorders. The principles and practice of medical genetics and genomics, and the management and treatment of patients and their families will be discussed. Utilizing exemplars, the module demonstrates the clinical utility of genomic data in healthcare settings. You will learn about contemporary approaches used to identify genetic causes of disease, with a focus on rare inherited diseases.
The module will also address the integration of genomic data into clinical pathways, emphasizing the impact of advances in genomic technologies on patient care. The role of genomics in care pathways will be explored from both patient and family perspectives, as well as the diagnostic and therapeutic implications of genomic data. Additionally, you will learn to identify patients with unmet diagnostic needs who may benefit from exome or genome sequencing and will be introduced to the complexities of interpreting genomic data in clinical contexts. The module will also cover key initiatives such as the development of genomic medicine services, and the infrastructure supporting incorporation of genomic testing into the NHS.
HPDM038: Molecular Pathology of Cancer and Application in Cancer Diagnosis, Screening and Treatment
This module covers the molecular mechanisms that underlie cancer development, growth and metastasis, and the differences between cancer types. It will explore the varied molecular and cellular actions of cancer treatments, the genomic factors affecting response and resistance to treatment and the research approaches to cancer drug development. The genomic basis for cancer predisposition will also be discussed, considering how this may impact patients and their families. This will include risk assessment, cancer screening, treatment and cancer preventative options.
The module aims to equip you with knowledge and understanding of the molecular mechanisms involved in cancer development and highlight how interrogation of a person’s own genome and the genome of neoplastic cells can facilitate the diagnosis and personalised treatment of cancer.
HPDM039: Pharmacogenomics and Stratified Healthcare
Pharmacogenomics and stratified healthcare should ensure that patients are offered the 'right treatment, for the right person, at the right time’. This module will provide you with an overview of the analytical strategies and techniques used in pharmacogenomics and explore some of the challenges and limitations in this field. It will consider current clinical practice as well as emerging technologies.
This module aims to describe the complexity of pharmacogenomics and its application in clinical practice. This will include tailoring drug treatment to improve patient response, and techniques to stratify patients at risk of adverse drug reactions. The module will use examples of known, validated pharmacogenomic tests, relevant to the use of drug treatments.
HPDM044: Ethical, Legal and Social Issues in Applied Genomics
This module is available via blended learning with contact days on-campus and additional resources and activities via our online platform.
The module will provide you with a framework for ethical understanding of medical genomics. An 'ethics in practice' approach will be taken. You will be provided with a platform of ethical understanding from which to consider issues of confidentiality, autonomy, disclosure, informed consent and justice. You will consider the impact of genomic technologies on individuals, families, and demographic groupings. The social implications of genetic testing and screening will be considered, especially in the context of reproductive technologies. Finally, you will be provided with a legal framework for the use of genetic data for research, diagnostic and therapeutic purposes.
Many genomic tests have wider implications for the patient and their family, particularly where these may have a predictive aspect, provide incidental information, and/or have potential for being misleading or increase uncertainty. You will explore the ethical, legal and social implications (ELSI) involved in genomic testing and in specific integrated pathways.
This module equips you with knowledge and skills to support patients undergoing genomic investigations. Working together through a mixture of lectures, discussions and practical group exercises, you build foundational counselling skills and learn how to apply them to different genomic scenarios. The course also introduces key practical tasks in the medical genomic pathway, including taking consent, interpreting results and documenting family history. Throughout the course we consider the social, personal and familial impact of these tests, exploring how we can support individuals and promote equity in genomic medicine.
Expect to be supported, challenged and to work together extensively in small groups. If you have any access needs that you would like to discuss, please contact the module lead. Due to the interactive and layered design of the course, attendance is essential for all four contact days.
This module is available either via blended learning with contact days on-campus, or as fully distance learning via our online platform. There may be some variation in scheduled teaching and learning activities depending on your mode of study.
The main challenge for application of genomic data is in its analysis and interpretation. In this module you will build on the knowledge and understanding gained in the Bioinformatics, Interpretation, Statistics and Data Quality Assurance module. You will learn how to use programming and scripting via the command line as well as the 'Galaxy' interface to formulate more complex research questions and analyse NHS data sets. You will gain a greater understanding of the different approaches to sequence data assembly and alignment and copy number variant and structural variant analysis.
The module will cover more advanced principles of informatics and bioinformatics applied to clinical genomics, how to find major genomic and genetic data resources for use in more complex data analysis, and use of programming and scripting via the command line. Theoretical sessions will be coupled with practical assignments of analysing and annotating predefined data sets. Upon completion of this module you will be eligible to base your MSc research project on data from the '100,000 Genomes Project'.
This module is delivered through a blended learning format with scheduled on-campus contact days, supported by online learning resources available through the University’s virtual learning platform. The module introduces the structure and function of the human epigenome, including key regulatory mechanisms such as DNA methylation, histone modification and chromatin remodelling, and their role in controlling gene expression. You will examine how the epigenome interacts with the genome and how epigenetic regulation contributes to normal cellular function. Building on these core principles, the module explores the role of epigenetic variation in human health and disease. You will investigate how the epigenome changes with ageing and in response to environmental and psychosocial exposures, and how these changes may influence disease risk and progression. The application of epigenetics in diagnosis, treatment and monitoring of disease, particularly in areas such as cancer, will also be examined. The module will also introduce the genomic technologies and bioinformatics approaches used to study the epigenome, highlighting how epigenomic data can contribute to understanding disease mechanisms. Throughout the module, current challenges and limitations in epigenetic research will be critically discussed, alongside emerging developments in the field.
Standalone module fees:UK: £1,300 per 15-credit module
Credit bearing modules: If you opt to take a non-accredited module and wish to then fully accredit this with the University of Exeter, you will need to pass the assessed elements of the course within 6 months of completion and there is an additional £200 accreditation fee.
Standalone module fees:International £2,850 per 15-credit module
Scholarships
The University of Exeter offers a wide range of scholarships to support your education, with £7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
University of Exeter Alumni Scholarship
We are pleased to offer the University of Exeter Alumni Scholarship, a scholarship for University of Exeter alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship worth 20% of the cost of your first year tuition fees.
We deliver transformative education that tackles health challenges of national and global importance.
Research
Our expertise ranges from utilising big data studies in 100,000s of individuals to discover new genetic variants associated with disease, to translating findings from genomic studies to improve patient care, to using genomics to understand the evolution of infectious disease and the social and ethical aspects of genomic innovation in the life sciences, health and medicine.
Genomics research at Exeter is world-leading and supports our educational strategy and our objective to develop and apply innovative research and training methods, with opportunities for undergraduate, postgraduate and work-placed learning in diverse fields ranging from data science to the ethical legal and social impact of genomics.
Teaching
Using a mix of learning formats, our modules each run over a six- to eight-week period and include at least six half days of intensive face-to-face teaching, interspersed with distance learning and independent study.
Learning
All learning will be patient focused, using clinical scenarios and a variety of learning and teaching methods to promote a wide range of skills and meet differing learning styles, including seminars, group work, practical demonstrations and exercises surrounding interpretation of data.
Teaching will be delivered by experts from a range of academic and health care professional backgrounds chosen to ensure a breadth and depth of perspective and giving a good balance between theories and principles, and practical management advice.
Facilities
This programme is based at the St Luke’s campus in Exeter, just a 15 minute walk from the city centre and just over a mile away from the Streatham Campus. The campus is close to the Royal Devon and Exeter Hospital and RILD building, which is home to the NHS funded Exeter Health Library. Students have studied at St Luke’s campus for over 150 years and the campus enjoys a vibrant atmosphere set around the lawns of the quadrangle. Facilities at St Luke’s campus include:
Jess is an Associate Professor and Programme Director for MSc Genomic Medicine. Her main research interest involves using genetics to explore causal relationships to improve our understanding of the complex relationship between metabolic health and mental health.
Caroline teaches on the core module Fundamentals in Human Genetics and Genomics within the MSc Genomic Medicine. Her main research interests are in the clinical application of genome-wide sequencing technologies for the diagnosis of rare diseases.
She is also a visiting scientist at the Wellcome Sanger Institute in Cambridge, and is on the management committee for the UK Deciphering Developmental Disorders Study (www.ddduk.org).
Vikki is a Senior Lecturer in Biomedical Sciences. She is the deputy programme lead for the MSc Genomic Medicine and the Senior Academic Tutor for postgraduate taught programmes. She is also module lead for Molecular Pathology of Cancer and Application in Cancer Diagnosis, Screening and Treatment, and Pharmacogenomics and Stratified Healthcare.
She is currently a regional Public Engagement Officer for the Royal College of Pathologists helping facilitate public engagement in pathology in the South West.
Vikki is the senior academic tutor for the postgraduate taught programmes in CMH, and is committed to excellent student support.
Emma is a Senior Lecturer and module lead for two modules on the programme; Omics Techniques and their Application to Genomic Medicine, and Epigenetics in Human Health and Diseases. Her current research focus is on identifying gene regulatory changes in brain disorders such as schizophrenia and Alzheimer’s Disease and developing new epigenetic techniques and protocols.
This course is suitable for anyone who is interested in pursuing a career or further study in genomics or health data science. We welcome students from broad backgrounds including biology, health sciences as well as students from computer science, maths, physics or engineering backgrounds with an interest in data science in the field of genomics.
With a focus on genomic medicine and data science, you will delve into the latest advancements in genomics and learn how to leverage data-driven insights to enhance patient care. From improving diagnosis to personalising treatment plans, you will gain a comprehensive understanding of how genomic knowledge translates into tangible benefits for patients. Additionally, you’ll acquire essential skills in disseminating knowledge to peers, patients and the public, empowering you to effectively communicate the impact of genomic precision medicine.
Career paths
Healthcare professionals will advance their careers with refined capabilities in genomic medicine and data science, poised to optimise patient care within the NHS and beyond. Students who are not healthcare professionals will gain key knowledge, understanding and skills to help secure employment or PhD positions in the fields of genomics, bioinformatics, or other medically-related research and development in either academia, pharmaceutical or biotech industries.
Careers support
You will have access to theCareer Zone, which will provide you with a wealth of contacts, support and training as well as the opportunity to meet potential employers at our regular careers fairs.
The majority of students are based at our Streatham Campus in Exeter. The campus is one of the most beautiful in the country and offers a unique environment in which to study, with lakes, parkland, woodland and gardens as well as modern and historical buildings.
Located on the eastern edge of the city centre, St Luke's is home to Sport and Health Sciences, the Medical School, the Academy of Nursing, the Department of Allied Health Professions, and PGCE students.
Our Penryn Campus is located near Falmouth in Cornwall. It is consistently ranked highly for satisfaction: students report having a highly personal experience that is intellectually stretching but great fun, providing plenty of opportunities to quickly get to know everyone.
