Master's Degree Scholarships

Applicants must have a confirmed place on a UK MSc programme in Health Data Science (or a closely related programme with a significant health data component). If you are unsure whether your programme is eligible please contact us at learn@hdruk.ac.uk

The programme is open to students studying at universities across the UK and is not restricted to specific institutions.

International students are welcome to apply, however the scholarship provides a maximum contribution of £10,000, and applicants should ensure they have a plan to cover any remaining tuition or living costs.

Students can be studying on either a full time or part time basis.

The scholarship provides a maximum of up to £10,000 per scholar, which is paid directly to the HEI for tuition fees.

This is the maximum available through this programme and HDR UK does not provide additional funding for part-time study, international tuition fee differences, or living costs.

No. HDR UK does not formally accredit or partner with specific universities for this programme.

We maintain a list of relevant UK Health Data Science Master’s programmes on our website to help prospective applicants identify suitable courses. However, other programmes may also be eligible.

If your course is not currently listed, please contact us with a link to the programme and we would be happy to review it for possible inclusion.

You can start preparing your application, but you will need to provide evidence of a confirmed place on a relevant MSc programme as part of the application process.

Yes. International students are welcome to apply provided they have secured a place on an eligible UK Health Data Science Master’s programme.

Please note that the scholarship contributes £10,000 directly towards tuition fees, so applicants should ensure they can cover any remaining tuition or living costs.

HDR UK does not provide predefined research project titles.

Scholars are expected to develop their project within their MSc programme, working with their university supervisor in line with the requirements of their course.

Projects should:

• Align broadly with the relevant disease area supported by the scholarship
• Be feasible within the scope of a taught MSc dissertation

Scholars will also be asked to submit a short abstract of their proposed project topic to HDR UK and the charity partner to ensure it aligns with the relevant disease area.

Academic supervision remains with your university.

Charity partners provide light-touch engagement with scholars throughout the scholarship year.

Scholars will be expected to:

• Share an abstract of their proposed project topic with HDR UK and the charity partner
• Engage with the charity partner during the year
• Share a copy of their completed project

Charity partners may also provide advice on research priorities in the disease area and may be able to suggest relevant research groups or experts.

However, academic supervision remains with your university supervisor.

The scholarship works best when students have some flexibility in choosing their research project.

If your programme offers very limited options for project topics, it may be difficult to align your dissertation with the disease area supported by the scholarship.

No. You do not need to have a fully developed project proposal when applying.

You should demonstrate interest in the disease area and how data science could contribute to research in that field.

The specific project will usually be developed later with your MSc supervisor and with guidance from the charity partner where appropriate.

You should apply to the disease area that most closely aligns with your interests and experience.

If your interests align with more than one disease area, you may submit separate applications and demonstrate your motivation for each within the relevant application form.

Strong applications typically demonstrate:

• Clear motivation to study Health Data Science
• Evidence of data related skills or experience
• Genuine interest in the relevant disease area
• Thoughtful ideas about how data science could contribute to research in that field

Applicants who provide specific examples from their experience tend to perform best in the selection process.

As a scholarship recipient you will be expected to:

• Fully engage with your Master’s programme
• Share an abstract of your proposed project topic with HDR UK and the charity partner
• Share a copy of your completed project
• Inform HDR UK and the charity partner if you intend to publish or present results

Where research outputs are published, they should comply with HDR UK’s Open Access Policy.

Scholars are also encouraged to engage with the HDR UK research community and relevant events during the scholarship year.

In the MRes in Biomedical Research (Data Science) you receive core training in AI/machine learning, multivariate statistics and chemometrics, and interdisciplinary training in big data analysis (multi-omics, electronic health records, medical imaging, natural language processing) to build skills towards a career in biomedical data science research. This programme allows you to do two research projects (October to March, and April to September) through which you will also develop your communication, presentation and grant-writing skills.

• Find out more.

This master’s course provides advanced skills in epidemiology and biostatistics and develops a knowledge of research methods commonly applied in epidemiology and public health.

Students will examine emerging research to build expertise in core epidemiological and statistical concepts to understand the distribution and causes of diseases in populations and explore possible prevention and control strategies.

This course is a chance to gain expertise in developing, applying and interpreting results from cutting-edge statistical and machine learning approaches for analysing and integrating complex sets of data that are emerging in the health field.

Delivered by international experts it equips students with both a sound theoretical and practical understanding of the needs and utility of health data analytic tools. The programme has a strong technical component, and will provide the complementary training for a career in health data sciences.

The MSc at King’s prepares you for a leading role in health data science with advanced training in statistics, machine learning and AI with emphasis on real-world applications.

You’ll work on a novel research project embedded within a research team, gaining hands-on experience with a wide range of real-world health data—including electronic health records, wearable technologies, omics, clinical trials, and digital biomarkers.

• Find out more here.

Learn to manage and analyse large, diverse datasets and develop quantitative, computational and practical data management and professional skills. Find out more

An MSc designed to help meet the growing demand for medical statisticians who can analyse health data to solve the biggest challenges in medicine.

From designing clinical studies to identifying the causes of diseases, it develops the specialist skills needed to play a vital role in global health and development.

This MSc is designed to prepare students for leadership or strategic positions in the NHS or wider public and private sector organisations. Its focus is on the practical implementation of health data in clinical settings, applications to health inequalities and quality improvement, and implications for public health and policy.

• Find out more.

This MSc programme enables students from healthcare and computational backgrounds to develop their health data science skills, supported by an interdisciplinary team of academics, NHS and industrial partners.

The MSc programme at Birmingham blends theoretical knowledge and practical experience, preparing graduates for impactful careers in the rapidly growing field of health data science. Students gain the skills in AI, health data and advanced computing needed to shape the future of the clinical and biomedical worlds.

An exciting mix of medical statistics and the latest developments in data science enabling students to engage with complex statistical and health data science challenges. Find out more 

Gain a broad education in methods from the mathematical, computational and statistical sciences that can be applied to answer scientific questions in biology and medicine. Find out more

A gateway to exciting careers in health data – the programme offers a genuinely interdisciplinary experience and an opportunity to gain cutting edge skills in health-related data. Find out more 

Acquire cutting-edge health data science skills and put them into practice in projects with world-renowned experts in statistical and health sciences. Find out more.

Medical statisticians are pivotal to the success of medical research and the development of new treatments. This MSc brings  the chance to learn the skills to help shape the future of medical research and public health. Lancaster’s world-leading researchers will provide you with a firm foundation in statistical theory alongside both classical and modern practical techniques.

A high-quality training in the analysis of genomic big data, from basic statistical and computational analytics, through bioinformatics to clinical trials. Find out more

MSc Programme in Health Data Science, University of Liverpool. Find out more here.

This MSc in Health Data Science is a full-time on-campus course that gives a broad grounding in data engineering, statistics, machine learning, and healthcare systems. It is delivered by staff across health informatics, biostatistics and machine learning groups. Topics of particular interest for further research include:

• digital epidemiology
• mobile health
• methods for analysis of electronic health records
• clinical prediction modelling
• causal inference
• clinical trials
• omics research

The St Andrews MSc is an opportunity to develop skills that will help in the transformation of healthcare. Students will be able be enable to:

• Prepare themselves for a career in data science and digital health
• Develop a more rounded understanding of digital health questions and concepts through interdisciplinary study
• Gain practical skills in medical data analysis and the use of digital technologies to address healthcare challenges.