DPhil Biomedical and Clinical Sciences (Oxford-GSK)

This programme is funded by GSK and provides fellows with three years of funding which is inclusive of university fees, clinical research salary on the Grade E63 or E64 scale and consumables. It is anticipated that up to three fellows will be appointed for Oct-2026 graduate admission. The therapeutic areas focus of the fellowships will be neurodegeneration, liver fibrosis and respiratory medicine.

Targeted Development of Data Science Capabilities

• Fellows will receive dedicated training in data science via the OBDS programme.
• Specific data science skills will be determined by individual projects, but it is expected that graduating fellows are proficient in a programming language (e.g. R or Python), understand the coding of healthcare records and approaches to access/analyses the data, and can selected the appropriate biostatistical techniques for the analysis of real-world data, multi-omic big data and the design of machine learning approaches. 

Project Parameters

• It is expected that the focus of projects will be the collection, analysis and interpretation of multi-omic data, with the leveraging of existing departmental infrastructure and personnel to support any laboratory work.
• Supervision will include relevant therapeutic and data science expertise, with representation from both Oxford and GSK.
• Projects will focus on a patient-centric approach to understanding disease endotypes and mechanisms of disease, thus enhancing future patient stratification and precision medicine strategies in drug development.

Therapeutic Areas and Scientific Themes

Neurodegeneration

The following diseases are within scope:

• Alzheimer’s disease
• Parkinson’s disease and Dementia with Lewy Bodies
• Amyotrophic lateral sclerosis

Scientific themes:

• Role of the CNS and peripheral immune system in neurodegeneration.
• Using data from human samples, identify potential mechanisms for drug intervention that differ based on disease stage.
• Discovery and validation of biomarkers (from human samples) reflecting various pathophysiologies that can be used to predict patient phenotype and track response to therapy. 

Liver Fibrosis

The following diseases are within scope:

• Steatotic liver disease to encompass metabolism associated steatotic liver disease (MASLD), alcohol related liver disease (ALD) and also MetALD.
• Other fibrotic liver diseases driven by hepatocellular injury considered in scope where these are used as a mechanism to cross-translate into steatotic liver disease.
• Emphasis should be placed upon advanced liver disease (F3 or cirrhosis) with inclusion of other phenotypes included as control populations.

Scientific themes:

• Mechanistic similarities and differences between alcohol and metabolically driven steatohepatitis and how these influence differing rates of disease progression.
• Predictors of and underlying mechanistic basis for fibrosis regression within the context of therapeutic intervention in advanced fibrotic liver disease.
• Circulating and/or imaging-based biomarkers indictive of therapeutic efficacy on fibrosis and inflammation.
• Translationally valid preclinical models of advanced fibrosis.

Respiratory Medicine

The following diseases are within scope:

• COPD
• Bronchiectasis
• ILD (comprising IPF, PPF, CTD-ILD)

Scientific themes:

• Using data from human samples to identify mechanisms involved in the progression of fibrotic ILDs
• Understanding the interplay between of inflammation and fibrosis in CTD-ILD and differences between the systemic and pulmonary compartments
• Circulating, VOC or imaging markers that predict disease progression or response to treatment in ILDs
• Predictors of exacerbators and fast disease progression for COPD
• Characterisation of COPD endotypes throughout disease course (early to late stage)
• Similarities and differences between mechanistic drivers of COPD and bronchiectasis
• Understanding differences between T2 high and T2 low respiratory diseases

APPROVED Projects (2026 ENTRY)

• A spatial and functional map of immune responses in MASLD, Met-ALD and AILD (Supervisors: Professor Paul Klenerman, Dr Emma Culver, Professor Ye Oo, Dr Aneesha Bandari, Dr Jeremy Cobbold, Dr Stephen Atkinson)
• Amyotrophic lateral sclerosis: biological drivers of a complex disease (Supervisors: Professor Kevin Talbot, Associate Professor Alexander Thompson, Dr Ruxandra Dafinca, Dr Avigail Taylor)
• Fibrosis Unmasked: A Metabolic Cell Odyssey in Liver Fibroblasts (Supervisors: Professor Chris Buckley, Professor Mark Coles, Dr Calliope Dendrou)
• Identifying Alzheimer's Disease Causal Gene Networks in Brain Vascular and Immune Cells (Supervisors: Professor Zameel Cader, Professor Laura Parkinnen)
• Modelling multi-omic effects in Parkinson’s Disease to validate putative novel PD genes and identify potential biomarkers of disease (Supervisors: Professor Jenny Taylor, Dr Dianne Newbury)
• Oxysterols and liver fibrosis (Supervisors: Professor Jeremy Tomlinson, Professor Leanne Hodson, Professor Ellie Barnes, Dr Steve Atkinson)
• Targeting temporal and spatial immuno-stromal pathways in lupus nephritis (Supervisors: Professor Katherine Bull, Dr Alex Clarke, Dr Kristina Clark, Dr Antony Psarras, Professor Chris Buckley)
• Tau and TDP-43 at cross-roads in neurodegeneration: Spatiotemporal interaction study in neurons (Supervisors: Dr Martina Hallegger, Dr Steph Fowler, Dr Avigail Taylor, Professor John Todd)
• The cellular interactions in a steatotic and inflammatory liver microenvironment that drives the progression and regression of hepatic fibrosis progression (Supervisors: Professor Ellie Barnes, Dr Emma Culver, Dr Alex Gordon-Weeks)
• Transcriptomic stratification for improved Motor Neuron Disease modelling in human iPSCs (Supervisors: Professor Kevin Talbot, Dr Martina Hallegger, Dr Avigail Taylor, Dr Ruxandra Dafinca)