The Pre-Doctoral Fellowship offers applicants who currently do not hold a Masters Degree the opportunity to undertake a fully funded master level course in a relevant research methodology.
The list below contains the names and contact details for a number of masters courses that could be deemed appropriate to undertake as part of the training and development of this Fellowship. It is not an exhaustive list and applicants may apply for other relevant courses as required.
For further information, please refer to the latest set of guidance notes listed on the NIHR website.
Please note: should you propose to undertake one of these courses as part of your training and development plan, this does not automatically guarantee funding for the Pre-Doctoral Fellowship, or a place on the listed course.
Last updated: 16th January 2023
Health Economics Masters
City, University of London
Contact: Victoria Serra-Sastre
Areas able to support: Victoria Serra-Sastre is a Senior Lecturer at the Department of Economics at City, University of London. Her main research interests are health economics and applied microeconometrics. Victoria’s main areas of research are on technology diffusion of health care technologies, and its impact on health outcomes and hospital performance. She also works on issues around retention of hospital workforce and productivity, and topics of maternal and child’s health.
University of York
Contact: Luigi Siciliani
Areas able to support: Luigi Siciliani is a Professor of Health Economics at the Department of Economics and Related Studies at the University of York, where he directs the MSc in Health Economics. He has specialised in health economics and micro-econometrics with a focus on healthcare providers. His research interests include waiting times for non-emergency treatment, hospital quality competition, contracting theory applied to health care, pay for performance and coordination between health and social care.
University of Birmingham
Contact: Dr Raymond Oppong
Areas able to support:
We run two MSc programmes: MSc Health Economics and Health Policy and MSc Health Economics and Econometrics. There are also a number of modules that are available as short courses: Introduction to Health Economics; Economic Evaluation of Healthcare; Statistics for Health Economics; Policy and Economics of Healthcare Delivery; Modelling for Health Economics.
We are interested in supervising anything related to health economics and have specific expertise in methods modelling, econometrics and methods for valuing outcomes and dis-utilities associated with screening but have a broad team with specific expertise in a range of clinical areas and methods and who are happy to support a full range of Health Economics related research.
University of Lancaster
Professor Céu Mateus
Support areas: Céu Mateus is a Professor of Health Economics at the Division of Health Research at Lancaster University. Her main research interests are health economics, health policy evaluation, and health technology assessment. Céu has a wide experience on the evaluation of digital technologies and their impact on the provision of health care and in improving access to care for certain population groups (elderly, ethnic minorities, rural populations, etc.)
University of Sheffield
Professor Alan Brennan
Support areas: Within the School of Health and Related Research (ScHARR), AlanBrennan (Professor of Health Economics and Decision Modelling) has been developing and applying modelling in support of healthcare decision-making nationally and internationally, across a large range of diseases, interventions, and policy issues for over 25 years. He is also involved with the management, design and delivery of the HEDM course.
Dr Rob Pryce
Support areas: Dr Rob Pryce is a Research Fellow and Programme Lead for the HEDM programme. His research interests are around the economics of addiction and addictive behaviours including alcohol, smoking, drug use, and gambling.
Mr Matt Scarborough
Support areas: Matt Scarborough is the course administrator. We are interested in supervising projects covering health economic modelling and evaluations (often cost-effectiveness analyses/health technology assessments) covering any clinical area and for a variety of types of intervention including new drugs, screening programmes, public health policies, and medical devices.
Medical Statistics Masters
University of Leicester
Support areas: Dr Stephanie Hubbard is an Associate Professor of Medical Statistics and joint course Director for the MSc in Medical Statistics. Her research interests are in the area of evidence synthesis for the evaluation of the effectiveness and cost-effectiveness of complex interventions, particularly in public health. The Biostatistics and Genetic Epidemiology Research Groups at Leicester deliver the MSc in Medical Statistics.
Methods in which we would be able to support fellows include:
- Survival Analysis;
- Health Technology Assessment;
- Health Economic Decision Modelling;
- Clinical Trials Methodology; Machine Learning;
- Analysis of linked Electronic Health Record data (“Big Data”);
- Causal Inference;
- Visualisation of Statistical Concepts, Data and Analyses results;
- and Statistical Methodology and Computation Development motivated by complex problems in genetics.
We have collaborations across many clinical and related disciplines with particularly strong collaboration in cancer survival, cardiovascular disease, public health and diabetes. We are happy to connect interested applicants with our academic staff.
University of Lancaster
Dr Andrew Titman
Support areas: Andrew Titman is Professor of Statistics and the research theme lead for Medical Statistics within the Department of Mathematics and Statistics. His main research interests are in survival and event history analysis, with a particular interest in methodology and applications of multi-state models. The Statistics group at Lancaster run the MSc in Statistics which includes a Medical pathway covering clinical trials, epidemiology, longitudinal data analysis and survival analysis. We would be able to support fellowship applications in a broad range of areas including survival analysis,
joint longitudinal-survival modelling, quality-of-life assessment, spatial epidemiology, epidemic modelling adaptive design of clinical trials, personalised medicine, and health-care monitoring technology. We have active collaborations both with the university's Faculty of Health and Medicine and with external clinical trials units.
London School of Hygiene and Tropical Medicine (LSHTM)
Support areas: Current areas of methodological research that the LSHTM Medical Statistics department would be able to support include: missing data, especially in longitudinal studies; propensity scores and other methods of adjustment for confounders; methods for causal inference (e.g. mediation analyses, methods for time-varying confounding adjustment); time- updated models relating disease events/biomarkers to prognosis; development of user-friendly prognostic risk scores; allowance for measurement error; small sample inference for mixed models. Methodological research in clinical trials includes: adaptive designs; non-inferiority trials and surrogate endpoints; cross-over trials; multiplicity of data (e.g. subgroup analyses, composite endpoints, repeated measures) in trials; statistical methods for the evaluation of complex interventions.
King's College London
Support areas: Daniel Stahl is Professor of Medical Statistics and Statistical Learning and lead of the Precision Medicine and Statistical Learning group. Zahra Abdulla is Senior Teaching fellow in statistics. They are academic program leads of the MSc in “Applied Statistical Modelling and Health Informatics, which is centred on the disciplinary strength and academic excellence of the Department of Biostatistics and Health Informatics located in the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. The MSc delivers a skill set and knowledge base in complex “multimodal” and “big data” analysis techniques, which are a recognised scarcity within UK Life sciences. Students will receive world-class training in core applied statistical methodology, machine learning and computational methodology. They will have the opportunity to apply their skills to real-life settings facilitated by the world-leading Institute of Psychiatry, Psychology and Neuroscience. Students can choose projects from a variety of research areas, such as health informatics, prediction modelling, clinical trials, causal modelling, psychometrics, epidemiology, structural equation modelling, natural language processing, machine learning, computational neuroscience and AI.
University of Sheffield
Prof Steven A. Julious
Support areas: Steven Julious is a Professor of Medical Statistics and a NIHR Senior Investigator. The MSc is an applied MSc which can be undertaken either full time or by distance learning. The MSc gives excellent statistical grounding and has formed part of the training programme for Pre- doctoral Fellows in Sheffield and at other universities (by distance learning) Students who complete the MSc go on to work in clinical trials - in academic or in industry settings - or continue their studies through a PhD.
University of Bristol
Support areas: Find out more on the website.
Clinical Trials Masters
University College London
Dr Hakim-Moulay Dehbi
Support areas: Statistics is a fundamental discipline in clinical trials. Statisticians ensure that study designs are statistically robust so that research questions can be answered. This online programme will provide an excellent grounding in statistics for clinical trials. Frequentist as well as Bayesian statistics will be covered. You will learn about all types of trials, from early to late phase trials, and from simple to complex interventions. This will be both from a design and analysis perspective. In addition, you will learn to code in R and STATA.
Operational Research Masters
University of Essex
Dr Yanchan Bao
Support areas: Dr. Yanchun Bao will be able to offer support in statistics, biostatistics and operational research. Find out more about this MSc.
University of Bristol
Support areas: The MSc will introduce the principles of modern epidemiology and its role in public health and other health-related disciplines. You will learn how to design and analyse experimental and observational studies covering aetiology, interventions, diagnosis and prognosis. There will be opportunities to learn about cutting-edge methods in causal inference and molecular epidemiology.
University of Newcastle
Support areas: You'll study a subject-specific module in clinical epidemiology. This provides a theoretical and practical understanding of: the value, theoretical basis and practicalities of epidemiology approaches to epidemiological research
London School of Hygiene and Tropical Medicine
Ian Douglas and Patrick Nguipdop-Djom
Support areas: Epidemiology is a key discipline for understanding and improving global health. Epidemiological methods underpin clinical medical research, public health practice and health care evaluation, investigation of the causes of disease, and evaluation of interventions to prevent or control disease. This programme covers both infectious and non-communicable disease epidemiology and has a global approach encompassing study in low, middle and high income settings.
University of Newcastle
Dr Katherine James
Support areas: The MSc Bioinformatics is a highly interdisciplinary programme built around computational approaches, including machine learning and Artificial Intelligence, for analysing the large volumes of data generated by multiple ‘omics technologies such as genomics, proteomics, etc. The programme has a strong emphasis on research, both in the core taught material and the dissertation project, which many of our students carry out in research labs across the whole University, or even in companies.