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ESRC White Rose DTP Studentships 2026/27

The Economic and Social Research Council (ESRC) is the UK's largest funding agency for research and postgraduate training relating to social and economic issues. The University of Leeds is part of the ESRC White Rose Doctoral Training Partnership, forming a collaboration between the Universities of Leeds, Sheffield, York, Bradford, Sheffield Hallam, Hull and Manchester Metropolitan. Through this partnership, the University offers a range of social science PhD studentships available to UK and international applicants. These studentships are available in seven named Thematic Interdisciplinary Training Pathways and can be held full-time or part-time. Various award types are offered: +3.5 Studentships for 3.5-year PhDs (for students with a social science Masters degree and 60+ credits of M-level social science research methods training); +3.75 Studentships for integrated PGCert/PhD programs (3 years 9 months for students with a social sciences Masters degree but fewer than 60 credits of M-level training); and 1+3.5 Studentships for a 1-year Masters programme followed by 3.5-year PhD (for students without a social science Masters degree). A range of studentships are available including WRDTP Pathway Studentships for impactful social science research, up to 2 WRDTP Advanced Quantitative Methods Studentships for cutting edge quantitative research, up to 2 Advanced Data Analytics Awards for researchers using cutting edge data analysis techniques or big data, and up to 2 WRDTP/Stuart Hall Foundation Studentships specifically for Black British students. All WRDTP programmes include an integral 3-month 'Research in Practice' placement as standard. The awards cover fees at standard UKRI rates, a maintenance grant (£20,780 in Session 2025/26 for full-time study, pro-rata for part-time), and a Research Training Support Grant for travel and research costs during the PhD. The award is open to all applicants including international students, though moving costs to the UK are not covered.

Functional data analysis with informative missingness (UK Only)

This PhD research project focuses on developing functional principal component analysis (FPCA) and multivariate FPCA (MFPCA) frameworks for functional data with informative missingness. The increasing availability of extensive datasets with variables measured over a continuum has opened new frontiers in research across disciplines. These datasets, known as functional data, are prevalent in fields ranging from environmental monitoring and education to biomedical sciences and engineering. However, analysing such data remains challenging due to their high dimensionality, multivariate structure, and critically, the presence of missingness that is not completely at random. This project aims to fill the gap by developing advanced statistical methods to handle informative missingness in functional data analysis. Real-world datasets often suffer from different types of informative missingness, and applying FPCA or MFPCA without accounting for these issues can lead to biased results, misrepresenting relationships among variables and undermining downstream analyses such as prediction, classification, and decision-making. The application will be within biomedical studies, such as Alzheimer's disease and scleroderma. The position offers a highly competitive EPSRC Doctoral Landscape Award providing full academic fees, together with a tax-free maintenance grant at the standard UKRI rate (£20,780 in academic session 2025/26) for 3.5 years. Training and support will also be provided, and candidates will be automatically considered for a School of Mathematics Scholarship.

EPSRC DLA Scholarship in the School of Computer Science

The School of Computer Science at the University of Leeds is offering a fully-funded, 3.5 year PhD studentship for UK fee-rated applicants, to start on 1 October 2026, as part of the EPSRC DLA scheme. This highly competitive EPSRC Doctoral Landscape Award provides full academic fees, together with a tax-free maintenance grant at the standard UKRI rate for 3.5 years, with training and support also provided. Applicants can propose research in any area of computer science for which the school is actively engaged in research. This includes five main research themes: Artificial Intelligence (robotics, biomedical analysis and imaging, reasoning, natural language processing), Computer Science in Biology, Medicine and Health (computational neuroscience, healthcare process analytics), Algorithms and Complexity (graph theory, scheduling), Distributed Systems and Services (cloud and edge computing, digital democracy), and Computational Science and Engineering (computational fluid dynamics, high-performance graphics, physics-informed neural networks). The School of Computer Science collaborates extensively with other universities and companies across the world, including Leeds Teaching Hospitals NHS Trust, and participates actively in the Alan Turing Institute and other national and international centres of excellence. The school holds the Athena Swann silver award for gender equality, and 99% of its research was classified as world-leading or internationally excellent in the most recent REF exercise. Up to 2 funded places are available. Selection is based on academic merit through the EPSRC Doctoral Landscape Award Competition. Applicants are strongly encouraged to contact supervisors for an informal discussion before making a formal application.