Health and Biomedical Informatics MSc – 2023 entry
Key information
Start date: September 2023
- Study mode and duration
- Full-time: 1 year
- Part-time: 2 years
Why choose this course
- Study a multi-disciplinary course combining expertise in informatics, artificial intelligence (AI), statistics, and the fields of epidemiological and biomedical, health and veterinary research
- Gain core informatic and AI skills to apply to global healthcare, biomedical and medical challenges
- Conduct a hands-on project that uses real-world data from large multidimensional studies such as UK Biobank
- Put theory into practice in our state-of-the-art facilities
- Champion our ‘One Health, One Medicine' approach.
What you will study
Our Health and Biomedical Informatics MSc will train you in developing and applying cutting-edge health informatics, bioinformatics and artificial intelligence (AI) technologies in biology, medicine and health. We’ll enable you to develop your quantitative, computational, and practical data analysis skills, while providing opportunities for further development of your professional skills. On this course, you’ll gain the knowledge and skills needed to manage and analyse large and diverse datasets across biomedical research and healthcare systems.
You’ll study topics including data science, epidemiology, and the fundamentals of biomedicine and AI, whilst gaining important cross-cutting skills. Our course is structured around existing large data resources, giving you the unique opportunity to build a portfolio of experiences in real world data handling, analysis, and interrogation. Course content will be based on data from a number of resources, including the world-leading UK BioBank.
It's important to understand where data emanates from in order to use it effectively. Within this course we teach the nature of omics techniques, electronic health records, and other methods followed by detail on how the data can be used correctly and appropriately. In addition to structuring practical sessions and module assessments on real-world health and biomedical data, we’ll also offer these data resources for specific and defined projects for your dissertation. All appropriate support will be offered to you to access data.
You’ll be able to choose from a range of different dissertation project topics that will cover both quantitative and qualitative research, applying a variety of methodologies covered throughout the programme. Dissertation projects will be supervised by a team with the appropriate methodological and domain expertise from across the Faculty of Health and Medical Sciences, the Surrey Institute for People Centred Artificial Intelligence, and from partners such as local NHS trusts, the Institute for Animal Health at Pirbright, and Zoetis. Projects will be themed into:
- Precision medicine and personalised care
- UK Biobank data analysis
- Digital health and decision support.
Facilities
Several of the modules you’ll study are complemented by hands-on, computer-based sessions and tutorials. These will support you in completing your coursework and in preparation for your assessments and dissertation project. We’ll provide you with computing support for any specialised software required during the course, as well as with accessing and handling the large datasets we’ll be using.
Dissertation projects will be offered across the Faculty of Health and Medical Sciences in different schools and research centres, including the University of Surrey’s School of Medicine, the Surrey Sleep Centre and the Surrey Clinical Trials Unit. There will be opportunities to work on clinical trial data and health informatics data from multidisciplinary programmes, such as combining health data with genomic and other omics data.
Dissertation projects will also be offered within the Digital Health theme, the Section of Systems Biology, and the Section of Statistical Multi-Omics. There are also opportunities in the School of Veterinary Medicine to undertake projects on animal health using multidimensional data analysis and digital health approaches for companion animals.
Teaching staff
You’ll be taught by academics who are active researchers, ensuring everything you learn is up-to-date and relevant to employers. These may include:
- Professor Nophar Geifman, Professor of Health and Biomedical Informatics
- Professor Anthony Whetton, Professor of Translational Biosystems
- Dr Haomiao Jin, Lecturer in Health Data Sciences
- Dr Adam Mahdi, Senior Lecturer in AI and Health Data Analytics.
Surrey Institute for People-Centred AI
Taking a different approach to much AI activity in the UK, our institute puts the needs of individuals and society at the very heart of everything it does. We believe that the starting point for AI should be people rather than technology. This people-centred approach drives our research and enables us to design AI technologies and systems which are ethical, responsible and inclusive.
Teaching
Your teaching will be delivered through a combination of:
- Case studies
- Lectures
- Practical tutorials
- Problem-based learning
- Online learning
- Seminars
- Workshops.
Outside of these, you’ll be expected to carry out independent study, including coursework and reading.
There may be occasions when the delivery of your teaching is supported by graduate teaching assistants. The University has a set of procedures that govern the use of postgraduate research students in this way.
Assessment
We use a variety of methods to assess you, including coursework, essays, examinations and presentations.
Check individual module information to see full details at a module level.
Study and work abroad
There may be opportunities to acquire valuable European experience by working or conducting research abroad during your degree or shortly afterwards. It is possible to do this in the summer period with an Erasmus+ grant working on your dissertation or as a recent graduate. In order to qualify your Erasmus+ traineeship must be a minimum of two months.
Careers and graduate prospects
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University. Our graduates have lifetime access to Surrey Pathfinder, our online portal for appointment and events bookings, jobs, placements and interactive development tools.
We’ll prepare you to become a multidisciplinary scientist with the skills required to develop informatic technologies and applications that transform biology, medical research, and healthcare. Our course will offer a gateway to a range of career opportunities using AI, data sciences, health and biomedical informatics in sectors including:
- Primary and secondary healthcare
- Health registries and public health
- Health, biomedical and bio high-tech industries
- Pharma companies
- Census data
- Digital health including medical devices or fitness/health applications
- Genomic, metabolomic and proteomic data
- Environmental data.
School
Research areas
Modules
Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability, student demand and/or class size caps.
The University operates a credit framework for all taught programmes based on a 15-credit tariff. Modules can be either 15, 30, 45, 75 and 120 credits, and additionally for some masters dissertations, 90 credits.
The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:
Optional modules for Year 1 (full-time) - FHEQ Levels 6 and 7
Students will develop their knowledge, understanding and hands-on analytical skills in this new field of health and biomedical informatics, as well as soft skills such as scientific presentation, dissemination, individual and group work, and multidisciplinary, and thereby enhance their career, via a series of interdigitating modules shown below. We will provide background knowledge on biology and medicine as required to contextualise the informatics into real world situations. At the heart of the programme is the use of the world leading resource at UK Biobank. Anonymised healthcare records, genome data, questionnaire responses (e.g. food preferences), biochemical data, proteomic data and metabolomic data are all available for teaching on statistics, machine learning, stratified medicine, data visualisation, omics data generation and usage, digital health, epidemiology, health and social care. These will provide students with a comprehensive introduction to the type of data that are typically collected across health and biomedical research and clinical practice; thereby equipping them with transferable skills in real-world settings. The precepts of health informatics and digital health, statistics and modelling, and Big Data, will be taught first; these will provide a strong foundation for students upon to build their learning journey through the second semester and their dissertation work. Following from the first semester, the Machine Learning and AI, as well as Reporting and Data Visualisation, Tutorials in Health Data Sciences, and Stratified Medicine and Biomedical Data Analysis modules will enhance the students¿ learning and skills development, by introducing more advanced topics in health and biomedical informatics. Throughout the process UK Biobank data will be used as a teaching aide.
Module title Credits
Introduction to Health Informatics and Digital Health 15
Machine Learning and AI 30
Tutorials in Health Data Science 15
Stratified Medicine and Biomedical Data Analysis 15
Statistics and Modelling for Health Data 30
Reporting and Data Visualisation 15
Big Data in Biomedicine and Health 15
Dissertation 60
Optional modules for Year 1 (part-time) - FHEQ Levels 6 and 7
Students will develop their knowledge, understanding and hands-on analytical skills in this new field of health and biomedical informatics, as well as soft skills such as scientific presentation, dissemination, individual and group work, and multidisciplinary, and thereby enhance their career, via a series of interdigitating modules shown below. We will provide background knowledge on biology and medicine as required to contextualise the informatics into real world situations. At the heart of the programme is the use of the world leading resource at UK Biobank. Anonymised healthcare records, genome data, questionnaire responses (e.g. food preferences), biochemical data, proteomic data and metabolomic data are all available for teaching on statistics, machine learning, stratified medicine, data visualisation, omics data generation and usage, digital health, epidemiology, health and social care. These will provide students with a comprehensive introduction to the type of data that are typically collected across health and biomedical research and clinical practice; thereby equipping them with transferable skills in real-world settings. The precepts of health informatics and digital health, statistics and modelling, and Big Data, will be taught first; these will provide a strong foundation for students upon to build their learning journey through the second semester and their dissertation work. Following from the first semester, the Machine Learning and AI, as well as Reporting and Data Visualisation, Tutorials in Health Data Sciences, and Stratified Medicine and Biomedical Data Analysis modules will enhance the students¿ learning and skills development, by introducing more advanced topics in health and biomedical informatics. Throughout the process UK Biobank data will be used as a teaching aide.
Module title Credits
Introduction to Health Informatics and Digital Health 15
Machine Learning and AI 30
Tutorials in Health Data Science 15
Stratified Medicine and Biomedical Data Analysis 15
Statistics and Modelling for Health Data 30
Reporting and Data Visualisation 15
Big Data in Biomedicine and Health 15
Dissertation 60
Timetable
Course timetables are normally available one month before the start of the semester. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day of the week (Monday – Friday). Wednesday afternoons are normally reserved for sports and cultural activities. Part-time classes are normally scheduled on one or two days per week, details of which can be obtained from the Academic Hive. View our Code of practice for the scheduling of teaching and assessment (PDF).
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Entry requirements
A minimum of a 2:1 UK honours degree or a recognised equivalent international qualification in computer science, informatics or biophysical sciences.
We'll also consider candidates who have studied veterinary medicine, human medicine, nursing or an allied health professions course.
Do I meet the requirements for this course?
We require you to submit a full application so that we can formally assess whether you meet the criteria published. Unfortunately, we are unable to provide an outcome based on an enquiry (via email, webform enquiry, phone or live chat).
International entry requirements by country
English language requirements
IELTS Academic: 7.0 overall with 7 in each element.
View the other English language qualifications that we accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.
Credit transfer
The University of Surrey recognises that many students enter their higher education course with valuable knowledge and skills developed through a range of professional, vocational and community contexts. If your experience exceeds the typical requirements for entry to the programme, a process called recognition of prior learning (RPL) may allow you to enter your course at a point appropriate to your previous learning and experience. If you can demonstrate that you have met the learning outcomes for specific modules through your previous learning, it may be possible to exempt you from those modules, and for you to be awarded credit based on your previous qualifications/experience. There are restrictions on RPL for some courses and fees may be payable for certain claims.
In some cases, prior knowledge and skills may allow applicants to join the start of a course without meeting the formal entry requirements.
Please see our code transfer and recognition of prior learning guide (PDF) and recognition of prior learning and prior credit web page for further information. Please email Admissions (admissions@surrey.ac.uk) with any queries.
Fees per year
Start date: September 2023
Full-time - 1 year
- UK
- To be confirmed
- Overseas
- To be confirmed
Part-time - 2 years
- UK
- To be confirmed
- Overseas
- To be confirmed
Please note:
- These fees apply to students commencing study in the academic year 2023-24 only. Fees for new starters are reviewed annually
- If you are on a two-year full-time MFA programme, or a two-year or three-year part-time masters programme (excluding modular/self-paced/distance learning), the annual fee is payable in Year 1 and Year 2 of the programme
- Annual fees will increase by 4% for each subsequent year of study, rounded up to the nearest £100, subject to any overriding applicable legislative requirements.
Payment schedule
- Students in receipt of a tuition fee loan: Will have their fees paid by the Student Loans Company in line with their schedule
- International students, or UK/EU students who have not taken out a tuition fee loan: Are required to pay their fees either in full at the beginning of the programme or in two instalments as follows:
- 50% payable 10 days after the invoice date (expected to be early October of each academic year)
- 50% in January of the same academic year.
The exact date(s) will be detailed on invoices. Students on certain part-time programmes, where fees are paid on a modular or stage basis, are not eligible to pay their fees by instalment.
- If you are sponsored: You will provide us with valid sponsorship information that covers the period of your study.
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Course | Status |
|---|---|
Health and Biomedical Informatics MSc Full-time, 12 September 2023 | Applications open Closing date: Monday 3 July 2023 |
Please note that we may have to close applications before the stated deadline if we receive a high volume of suitable applications. We advise you to submit your application as soon as it is ready. | |
Health and Biomedical Informatics MSc Part-time, 24 September 2023 | Applications open Closing date: Monday 3 July 2023 |
Please note that we may have to close applications before the stated deadline if we receive a high volume of suitable applications. We advise you to submit your application as soon as it is ready. | |
Admission information
Our postgraduate admissions policy* provides the basis for admissions practice across the University and gives a framework for how we encourage, consider applications and admit students. You can also read our postgraduate applicant guidance.
Terms and conditions
When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our Charter, Statutes, Ordinances, Policies, Regulations and our terms and conditions. These terms and conditions are provided in two stages: first when we make an offer and second when students who have accepted their offers register to study at the University. View our offer terms and conditions and our registration terms and conditions (PDF) for the 2022/2023 academic year as a guide as to what to expect.
Please note: the offer terms and conditions and registration terms and conditions which you will be asked to agree to may be different from those detailed in the examples. Our offer terms and conditions will generally be available in the September of the calendar year prior to the year in which you begin your studies. Our registration terms and conditions will be available at the start of each academic year and will vary to take into account specifics of your course and changes for the specific academic year.
Disclaimer
This online prospectus has been prepared and published in advance of the academic year to which it applies. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing but changes (for example, to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read our full disclaimer.
Course location and contact details
Campus location
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Address
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Surrey GU2 7XH