Internet Explorer is no longer supported by Microsoft. To browse the NIHR site please use a modern, secure browser like Google Chrome, Mozilla Firefox, or Microsoft Edge.

NIHR Pre-doctoral Fellowship Potential Supervisors 2022


19 January 2022


1.2 - February 2022


When applying for the Pre-Doctoral Fellowship, it is expected that applicants will have the help and support from two or more supervisors when putting together the application, in particular, details of the training and development programme.

Supervisors will also play an active role in supporting the applicant throughout the duration of the fellowship itself. At least one of the intended supervisors must be within the selected research methodology proposed for study. 

For those applicants that have yet to identify a supervisor, the list below contains the names and contact details of individuals willing to provide support in putting together an application, and with undertaking the fellowship. This list is not exhaustive and applicants may approach other potential supervisors as required.

For further information, please refer to the latest set of guidance notes listed on the Fellowship Programme page.




Areas able to support

Lucy Smith University of Leicester I am able to support medical statistics or mixed methods research particularly relating to improving maternal and infant health such as statistical methodology around the measurement and monitoring of adverse pregnancy outcomes, qualitative research to understand parents’ and clinicians’ experiences of pregnancy loss, neonatal mortality and preterm birth and the use of large-scale routine health data to monitor and reduce inequalities in health.
Hareth Al-Janabi University of Birmingham Methods support health economics, especially supporting applications relating to:
  • Economics of mental health
  • Informal/family care
  • Qualitative and other innovative research methods in health economics
  • Economic decision-making in health organisations
  • Process tracing 
Karla Hemming University of Birmingham I am a statistician with an interest in cluster randomised trials. My research interests range from statistical (including sample size and analysis issues) to the more practical (including reporting, bias and ethical issues).
Tracey Sach University of East Anglia I am interested in supervising someone who would like to learn about economic evaluation and/or outcome measurement. I have a particular interest in these methodologies as applied to dermatology, rehabilitation and older people.
Emma Frew University of Birmingham I am a NIHR Research Professor in health economics with a particular interest in using economics to inform policy to tackle population obesity. I work closely with local authorities, commercial stakeholders and third sector organisations. I am especially interested in supporting applications relating to methodological challenges of using health economics in non-health contexts.
Diana Baralle University of Southampton  I am a clinical academic in genetics and genomics. I work on finding new disease gene associations for rare diseases and deep phenotype of them. My lab is involved in bringing RNA and splicing into diagnostics using wet lab, RNA seq and bioinformatics, expanding on functional genomics. I have also used RNAseq in COVID, looking for biomarkers of disease, severity and response to treatment.
Christian Mallen Keele University Dean of Keele Medical School and NIHR Research Professor in General Practice.
Rupert Pearse Queen Mary, University of London We can offer particular experience in the day to day conduct of clinical trials in areas of acute medical care such as surgery, anaesthesia, trauma and emergency medicine. Our particular strength is in applied health research including pragmatic trials and mixed methods research which combine qualitative and quantitative methods. We are affiliated to the Pragmatic Clinical Trials Unit at QMUL, allowing co-supervision by an appropriate methodological expert if needed.
Niina Kolehmainen Newcastle University Strong methods expertise in the development and evaluation of complex non-drug interventions in the context of children and families, and access to co-supervisors with complementary clinical, life-sciences and behaviour change expertise as required.
Daniel Prieto Alhambra University of Oxford I am Theme Lead for Observational Research at the Centre for Statistics in Medicine, University of Oxford. I have expertise in the analysis and interpretation of routinely collected data including national and international electronic medical records, registries, and audit/s data for research. Please visit the NDORMS Daniel Prieto Alhambra webpage for more details.
Owen Arthurs Great Ormond Street Hospital I specialise in post mortem imaging and minimally invasive autopsy in children, so can offer both quantitative imaging-based diagnostic accuracy projects, as well as qualitative or mixed methods research around parental choice and experience. For example, current research into parental experience and preference around bringing new imaging methods into clinical practice, with strong qualitative research infrastructure support from across UCL.
Sian Taylor-Phillips University of Warwick I specialise in evaluating population screening programmes, such as the NHS cancer screening programmes (Breast, Cervical and Bowel), newborn blood spot screening and antenatal screening. I evaluate proposed new screening programmes and screening tests, through primary research such as observational studies and randomised controlled trials, and through systematic review of the published literature. My particular specialism is breast cancer screening.
Céire Costelloe Imperial College
  1. Routine dataset
  2. Causal inference
  3. Natural experiments and quasi experimental design
  4. Interest in infection in particular
Lorna Fraser University of York My areas of expertise lie in the secondary data analyses of routinely collected health and administrative datasets especially, but not exclusively, in areas of child health research.
Dr Rebecca Kearney University of Warwick Dr Kearney is an NIHR senior award holder, associate director and clinical trialist within Warwick Clinical Trials Unit. Main expertise is leading the design and delivery of randomised controlled trials evaluating the clinical and cost effectiveness of complex interventions in health care. Collaborating with senior health economists, statisticians and other clinical trialists in this academic environment. Dr Kearney would be able to co-supervise potential applicants wanting to develop expertise in any of these areas.
Richard Meiser Stedman University of East Anglia I am a clinical psychologist who leads trials of complex interventions, i.e. psychological therapies for emotional disorders, particularly in young people. I also have interest in interventions with parents and low intensity intervention, e.g internet-delivered treatments for mental health.
Nuala McGrath University of Southampton I can support projects using advanced quantitative analyses of population health data or mixed methods research to explore the value of couples-focused behaviour change strategies for health intervention research and practice; and the design and evaluation of couples-focused interventions to improve adult health.
Katherine Woolf University College London I can support a project using multivariate statistical techniques to analyse large scale longitudinal administrative data on medical students and doctors; for example my current research is looking at how medical school choice and application success varies by social background. Please visit the UK Medical Applicant Cohort Study Wordpress.

The studentship would be co-supervised by Dr Henry Potts who is Deputy Director of UCL’s Centre for Health Informatics and Multiprofessional Education and a chartered statistician. 
Aki Tsuchiya University of Sheffield Aki Tsuchiya is a Professor of Health Economics based at the University of Sheffield, with a joint appointment between the Department of Economics at the School of Health and Related Research. She is a co-Director of the Centre for Wellbeing in Public Policy at the University, and a member of the EuroQol Group.  She has extensive experience teaching health economists to economists at both the undergraduate and postgraduate levels, and supervising research students.

Aki’s methodological research interests include:
  • measuring, valuing, and modelling health and wellbeing outcomes, and inequality aversion
  • incorporating equity concerns into social welfare functions
  • normative economics of health, public health and beyond.
Professor Sue Jowett University of Birmingham Professor of Health Economics. Specialises in applied trial and model-based economic evaluation. Broad clinical area of interest is chronic disease with emphasis on chronic respiratory disease, musculoskeletal disease and cardiovascular disease. Other linked areas of interest are multimorbidity and health economic aspects of air pollution.
Dr Louise Jackson  University of Birmingham Senior Lecturer in Health Economics. Louise Jackson’s research interests relate to methods of economic evaluation, and she is particularly interested in methodological issues relating to the evaluation of public health and digital health interventions. Louise’s applied areas of interest include sexual health, obstetrics and gynaecology, women’s health and global health.
Professor Sabine Landau (previous and ongoing supervision: 8 PhD, 1 NIHR doctoral fellow, 1 NIHR Pre-doctoral Fellow)                                        Professor Ulrike Schmidt (previous and ongoing supervision 33 PhD students, 1 NIHR Pre-doctoral Fellow)
King’s College London Sabine Landau is Professor of Biostatistics at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London and leads a research programme on causal modelling and evaluation. Ulrike Schmidt is a Consultant Psychiatrist, Professor of Eating Disorders and NIHR Senior Investigator. We have collaborated on numerous trial evaluations of interventions to improve outcomes for patients with eating disorders, providing a unique UK data resource that can be explored to gain insights beyond treatment effectiveness (including data from the NIHR ARIADNE, TRIANGLE and DAISIES trials).                                                                                                                                                      We offer a methodology training programme in causal modelling and efficacy and mechanisms evaluation. The fellow will be formally trained as a statistician/data scientist in applied health research by attending the MSc in Applied Statistical Modelling and Health Informatics. In addition, by working on a project as part of our collaborative team of clinicians, eating disorders researchers and statisticians, the fellow will have the opportunity to gain practical experience. The research team already knows that the treatments for Anorexia Nervosa and other Eating Disorders are effective but now wish to investigate the underlying mechanisms to understand for whom and how treatments work. Such knowledge can help clinicians target the right patients and further develop complex interventions for greater benefit. For example the project will address research questions such as “What aspects of the therapy experience bring about improvements in eating disorder symptoms?” and “Which psychological variables should be targeted to restore well-being and healthy weight?”. The COVID pandemic has led to dramatic increases in new eating disorders presenting, as such the questions addressed in this project are more pertinent now than ever.
Professor Daniel Stahl (previous and ongoing supervision: 8 PhD, 7 DClinc Psych, 3 NIHR Pre-doctoral Fellows),  Dr Ewan Carr, Dr Raquel Iniesta (previous and ongoing supervision: 2 PhD, 8 MSc)  King’s College London Daniel Stahl is Professor in Medical Statistics and Statistical Learning and is the lead of the "Precision medicine and Statistical learning" research group. He recently established the “Prediction Modelling group” in the NIHR Maudsley British Research Council (BRC). Ewan Carr is Research Fellow at the Department of Biostatistics and Health Informatics, King’s College London. He contributes to several BRC themes including Prediction Modelling and Topological Data Analysis. Raquel Iniesta is BRC lecturer in statistical learning at the department of Biostatistics and Health Informatics, King’s College London. She recently established the “Topological Data Analysis for Machine Learning group”. Based in the Department of Biostatistics and Health Informatics, we offer a methodology training programme in prediction modelling at the Institute of Psychiatry, Psychology and Neuroscience, King's College London.                                                                                        The fellow will be trained as a statistician in applied health research by attending the MSc in Applied Statistical Modelling and Health Informatics. Within our collaborative team of statisticians, health informaticians and our close collaborations with clinicians from across the IoPPN, the fellow will have the opportunity to develop dynamic prediction models using clinical electronic health records using the Clinical Record Interactive Search (CRIS) system that has been developed for use within the NIHR Maudsley Biomedical Research Centre (BRC). Dynamic models allow us to predict health outcomes, such as the development of psychosis or recurrence of depression, using repeated measures of relevant predictors over time. Importantly, this approach allows the model to be continuously updated when new longitudinal measurements become available. The fellow will work closely on current research projects in close collaboration with clinicians who will provide expert knowledge in the clinical domain. Existing applications include work in psychosis and antidepressant treatment response.
Dr Kimberley Goldsmith (previous and ongoing supervision: 2 PhD, 1 MSc, 2 DClinPsy)
Dr Nicola Metrebian (previous and ongoing supervision: 3 PhD, 10 MSc)Dr John Strang (previous and ongoing supervision: 10 PhD, 4 MSc)
King’s College London We would like to offer a methodology training programme at the Institute of Psychiatry, Psychology and Neuroscience, King's College London.The programme will focus on using causal modelling to answer questions of interest in the study of heroin addiction treatments. We have data already with evidence of effectiveness, but we need now to investigate nature and direction of causality.                                                                                                    The fellow will attend the MSc in Applied Statistical Modelling and Health Informatics in the Biostatistics & Health Informatics Department to be trained as a data scientist and statistician. The fellow will also have opportunities to study causal questions of interest in large trials of contingency management for addiction, such as ConMan and PRAISe. This would include methods such as mediation analysis to understand how contingency management has effects on important outcomes, and instrumental variable and other methods to study aspects of treatment process and adherence. The results of such analyses will empirically inform targeted treatment refinement. Data on other types of addiction management strategies will also be available to the fellow.
Professor Richard Emsley King’s College London Richard Emsley is an NIHR Research Professor and Professor of Medical Statistics and Trials Methodology at the Institute of Psychiatry, Psychology and Neuroscience.My research interests are in clinical trials methodology, and developing statistical methods for efficacy and mechanisms evaluation using causal inference approaches. I develop novel clinical trial designs which aim to answer questions about treatments more quickly and using fewer patients. The applications of these methods include randomised trials of complex interventions in mental health, and trial designs and associated analysis methods in precision medicine.                                                                                            I am keen to supervise people in the area of clinical trials methodology, and as part of the supervisory team can provide links with outstanding clinical researchers in psychosis, developmental disorders or self-harm.
Professor Richard Dobson, Zina Ibrahim King’s College London Richard Dobson's research focuses on the use of data (e.g. omics, electronic health records, smartphones and wearables) to transform the delivery of healthcare by addressing some of the fundamental uncertainties of clinical medicine: How do we diagnose disease and its sub-types? Is this intervention effective? How do we personalise care?The research has required the extensive use of computational approaches such as machine learning, the creation of software tools, development of a hospital development environments and large private cloud infrastructure to enable integration of patient datasets.                                                                                                                        In a team led by Professor Richard Dobson (Department of Biostatistics and Health Informatics), Zina Ibrahim offers methodological training in the theory, application and design of Machine Learning (ML) applications aiming to uncover knowledge from the vast amount of data available within the healthcare ecosystem.                                                                                                      In a collaborative team of Informaticians, medical scientists and clinicians, the fellow will have the opportunity to design robust ML-driven applications for the early prediction of adversity in response to treatment, as well as the prediction of hospitalisation outcomes from time-series data housed within electronic hospital records (EHRs). The team has already established a strong body of work in the prediction of hospitalisation outcomes in patients with sepsis, pneumonia and those infected with COVID-19. The projects will also develop unsupervised exploratory algorithms to answer questions such as: “how do subphenotypical traits influence the prevalence of a given outcome in a patient population?”  and “how do I design ML pipelines that are explainable and trustworthy for actual use in clinical settings?”
Raquel Iniesta King’s College
London Raquel Iniesta is BRC Senior Lecturer in Statistical Learning at thedepartment of Biostatistics and Health Informatics, King’s College London. She leads the “Topological Data Analysis for Machine Learning working group”.                                                                                                                                                  Based in the Department of Biostatistics and Health Informatics, the fellow will be trained as a statistician in applied health research including prediction modelling, machine learning and topological data analysis by attending the MSc in Applied Statistical Modelling and Health Informatics, and the departmental talks and seminars.                                                                                                                                                    Thanks to our collaboration with clinicians from across the IoPPN and Kings College London, the fellow will have the opportunity to develop topological machine learning models to identify subgroups of patients of interest (for example good vs bad responders to a drug) using data from clinical trials and clinical electronic health records from the Clinical Record Interactive Search (CRIS) system that has been developed for use within the NIHR Maudsley Biomedical Research Centre (BRC). Topological Data Analysis is a recent and promising field that allows us to extract information from big datasets by inspecting their shape. Existing applications include works in cancer and antidepressant treatment response. The fellow will work closely with mathematicians, computer scientists and clinicians that will provide expert knowledge in the theoretical and clinical domains.
Dr Lazaros Andronis University of
Warwick I'll be able to support prospective pre-doctoral students interested in topics related to:
  • Methods of economic evaluation in health care (with a particular interest in the evaluation of interventions targeting children and young people)
  • Measurement of costs borne by patients and their families (with a special interest in the value of time forgone due to seeking or receiving care)
  • Identification and measurement of patients; preferences for process outcomes (e.g. continuity of care, access, convenience etc).
  • Im happy to engage with prospective students to formulate research questions tailored to their particular interests and advise on suitable training and development plans.
Professor Penny Whiting University of
Bristol I am an Associate Professor in Clinical Epidemiology based in Population Health Sciences, Bristol Medical School. My research interests focus on diagnostic test evaluation, systematic reviews and developing tools to assess risk of bias in epidemiological studies. I also lead the MSc Epidemiology at University of Bristol. Please contact directly for further information. I am able to support projects in Systematic Reviews; Diagnostic Test Evaluation.
Professor Steven A. Julious University of
Sheffield Ability to support areas relating to Clinical Trials, Study Design, Sample Size Calculations, Meta-analysis and Asthma Epidemiology.
Nicholas Latimer University of
Sheffield NicholasLatimer is a Professor of Health Economics based at the School for Health and Related Research, University of Sheffield. His research interests include:
  • Survival analysis in the context of health technology assessment
  • Causal inference methods to estimate comparative effectiveness from real world data sources
Professor Stephen  Walters University of
Sheffield Ability to support areas relating to Design, conduct, analysis,and reporting of trials of complex interventions. Design, assessment, analysis and interpretation of patient reported outcomes in clinical trials and cluster randomised controlled trials.
Ines Rombach University of
Sheffield Ability to support areas relating to RCT design, analysis and interpretation; analysis of incomplete data and sensitivity analysis for missing data; Trials within cohort studies (TWICS).
Mike Bradburn University of Sheffield Ability to support areas relating to General considerations for Sheffield RCTs Generalisability/external validity of RCTs and survival analysis.
Rachel Phillips Queen Mary
University of
London Senior lecturer in medical statistics working on applied clinical trials and trials methodology. I am interested in supervising individuals interested in undertaking a project related to the area of adverse events in clinical trials.