About this course
MSc Personalised Medicine equips you with a 360-degree skill set across biomedical science, data science and clinical practice to advance your career in the life sciences.
This online course will expand your scientific expertise and skills and can support your continuing professional development for career enhancement.
It is aimed at graduates wanting to broaden their skills or upskill in key areas.
MSc Personalised Medicine is a Master’s programme that can be taken in 1 year full-time or across 2 years part-time. Both full-time and part-time programmes have two intakes and can be started in September or January.
This is a flexible, modular, credit-bearing programme that can be studied to achieve a range of postgraduate qualifications.
- By completing 8 modules and a research project to standard you can graduate with the full Masters (MSc).
- By completing 8 modules to standard without the research project you can graduate with Postgraduate Diploma (PgDip).
- By completing 4 modules without a research project, you can graduate with a Postgraduate Certificate (PgCert).
- Interested students are also welcome to complete individual modules as short courses.
This course will give you an in-depth understanding of disease systems, molecular pharmacology, genetic/proteomic biomarker discovery and validation, bioinformatics and data analytics applied to large patient and ‘omic’ datasets ('big data').
You will exit this course with a highly sought-after combination of expertise in biomedicine, bioinformatics and data analytics and will be well-equipped to become part of a rapidly expanding workforce on the cutting edge of scientific and medical progress. You will be well positioned for a career in research, the health service, and the pharmaceutical and diagnostics industries.
The programme has oversight from a dedicated Employer Advisory Board, comprising over 15 industrial partners located throughout the UK, Ireland and the US, including companies like Randox Laboratories, Almac Diagnostics, Illumina, Diaceutics and Cirdan.
MSc Personalised Medicine is delivered by a research active lecturing team, all with PhDs in relevant subject areas, who have professional body recognition and lead active research programmes in Personalised Medicine.
Students will study the following modules.
- MPM700: Clinical translation & regulatory pathways (15 credits). We explore the theory of prognostic clinical decision making in the context of current and future applications for personalised medicine. This module also details the regulatory and clinical guidance that ensures the safe and evidence-based testing.
- MPM701: Introduction to Personalised Medicine & Pharmacogenomics (15 credits). Exploring an important and emerging area of personalised medicine, this module focuses on how genetics affects drug metabolism, reviews the methods of biomarker discovery/development and explores the challenges of personalised medicine research and its introduction into society.
- MPM702: Multi-omics methods (15 credits). Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.
- MPM703:Research Ethics & Governance(15 credits). Providing an understanding of the importance of ethics and governance in clinical and research studies, this module covers the regulatory processes involved in research governance and provides students with an opportunity to experience an ethics review in a research application.
- MPM704: Biomedical Informatics (15 credits). This module teaches the theory and application of core biostatistics and bioinformatics techniques used across academia and industry in project planning, analysis and evaluation. It introduces the R coding language and explores how it can be used to implement analysis.
- MPM705: Clinical Trials Design and Patient Recruitment (15 credits).Providing the ability to critically evaluate clinical trial design, analysis, reporting and quality assurance, this module explores in depth the process of patient recruitment and the regulatory and ethical processes involved.
- MPM706: Healthcare Economics & Innovation (15 credits). Exploring the vital importance of economics in healthcare provision, this module focuses on the financial costs, benefits and limitations of delivering healthcare and introducing personalised medicine. This includes the economic models that underpin big pharma as well the importance of entrepreneurship and small medium enterprises in driving forward healthcare innovation.
- MPM707: Health Informatics & Data Science (15 credits). This module introduces the techniques needed to be able to work with high dimensional data (big data) and the mathematics that underpins the fundamental data science. Coding in Python, we learn how to analyse data and explore machine learning/AI based analysis
- MPM708: Research Project (60 credits).Undertaking a research project with one of our research active staff, in this module students will undertake a contemporary and novel research project in a topic related to personalised medicine.
Attendance
This course is fully online.
Start dates
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October 2026
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January 2027
Teaching, Learning and Assessment
Teaching is delivered by staff primarily through lectures, tutorials and practical activities and independent reading.
All course materials are available online, offering you the flexibility to study at your own pace.
The course is assessed 100% by coursework through multiple assessment formats and feedback will be provided within 20 working days for each piece of assessment, following Ulster University policy. Each module must be passed at or above a mark of 50%.
All students are assigned a studies advisor who provides personal support and pastoral care during their studies.
The content for each course is summarised on the relevant course page, along with an overview of the modules that make up the course.
Each course is approved by the University and meets the expectations of:
Attendance and Independent Study
As part of your course induction, you will be provided with details of the organisation and management of the course, including attendance and assessment requirements - usually in the form of a timetable. For full-time courses, the precise timetable for each semester is not confirmed until close to the start date and may be subject to some change in the early weeks as all courses settle into their planned patterns. For part-time courses which require attendance on particular days and times, an expectation of the days and periods of attendance will be included in the letter of offer. A course handbook is also made available.
Courses comprise modules for which the notional effort involved is indicated by its credit rating. Each credit point represents 10 hours of student effort. Undergraduate courses typically contain 10, 20, or 40 credit modules (more usually 20) and postgraduate courses typically 15 or 30 credit modules.
The normal study load expectation for an undergraduate full-time course of study in the standard academic year is 120 credit points. This amounts to around 36-42 hours of expected teaching and learning per week, inclusive of attendance requirements for lectures, seminars, tutorials, practical work, fieldwork or other scheduled classes, private study, and assessment. Teaching and learning activities will be in-person and/or online depending on the nature of the course. Part-time study load is the same as full-time pro-rata, with each credit point representing 10 hours of student effort.
Postgraduate Master’s courses typically comprise 180 credits, taken in three semesters when studied full-time. A Postgraduate Certificate (PGCert) comprises 60 credits and can usually be completed on a part-time basis in one year. A 120-credit Postgraduate Diploma (PGDip) can usually be completed on a part-time basis in two years.
Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures you can expect at least 3 contact hours per week (lectures/seminars/tutorials). Laboratory classes often require a greater intensity of attendance in blocks. Some modules may combine lecture and laboratory. The precise model will depend on the course you apply for and may be subject to change from year to year for quality or enhancement reasons. Prospective students will be consulted about any significant changes.
Assessment
Assessment methods vary and are defined explicitly in each module. Assessment can be a combination of examination and coursework but may also be only one of these methods. Assessment is designed to assess your achievement of the module’s stated learning outcomes. You can expect to receive timely feedback on all coursework assessments. This feedback may be issued individually and/or issued to the group and you will be encouraged to act on this feedback for your own development.
Coursework can take many forms, for example: essay, report, seminar paper, test, presentation, dissertation, design, artefacts, portfolio, journal, group work. The precise form and combination of assessment will depend on the course you apply for and the module. Details will be made available in advance through induction, the course handbook, the module specification, the assessment timetable and the assessment brief. The details are subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.
Normally, a module will have 4 learning outcomes, and no more than 2 items of assessment. An item of assessment can comprise more than one task. The notional workload and the equivalence across types of assessment is standardised. The module pass mark for undergraduate courses is 40%. The module pass mark for postgraduate courses is 50%.
Calculation of the Final Award
The class of Honours awarded in Bachelor’s degrees is usually determined by calculation of an aggregate mark based on performance across the modules at Levels 5 and 6, (which correspond to the second and third year of full-time attendance).
Level 6 modules contribute 70% of the aggregate mark and Level 5 contributes 30% to the calculation of the class of the award. Classification of integrated Master’s degrees with Honours include a Level 7 component. The calculation in this case is: 50% Level 7, 30% Level 6, 20% Level 5. At least half the Level 5 modules must be studied at the University for Level 5 to be included in the calculation of the class.
All other qualifications have an overall grade determined by results in modules from the final level of study.
In Masters degrees of more than 200 credit points the final 120 points usually determine the overall grading.
Figures from the academic year 2022-2023.
Academic profile
Our course is delivered and managed by the following team. All team members are Fellows or Senior Fellows of Advance HE, the professional body for higher education in the UK.
- Dr Sarah Atkinson, Senior Lecturer, LinkedIn Profile.
- Professor David Gibson, Professor of Personalised Medicine (Rheumatoid Arthritis), LinkedIn Profile.
- Dr Catriona Kelly, Senior Lecturer in Personalised Medicine (Diabetes), LinkedIn Profile.
- Dr Victoria McGilligan, Senior Lecturer in Personalised Medicine (Inflammatory Disease), LinkedIn Profile.
- Dr Elaine Murray, Associate Course Director, Senior Lecturer in Personalised Medicine (Mental Health), LinkedIn Profile.
- Dr Steven Watterson, Course Director, Lecturer in Computational Biology, LinkedIn Profile.
- Dr Shu-Dong Zhang, Associate Course Director, Senior Lecturer on Personalised Medicine (Bioinformatics), LinkedIn Profile.
The University employs over 1,000 suitably qualified and experienced academic staff - 60% have PhDs in their subject field and many have professional body recognition.
Courses are taught by staff who are Professors (19%), Readers, Senior Lecturers (22%) or Lecturers (57%).
We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic and learning support staff (85%) are recognised as fellows of the Higher Education Academy (HEA) by Advance HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.
The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise. The precise staffing for a course will depend on the department(s) involved and the availability and management of staff. This is subject to change annually and is confirmed in the timetable issued at the start of the course.
Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.
Figures from the academic year 2022-2023.
