Investigating cross-tissue and cross-disease immune mechanisms using single-cell/spatial multiomics & machine learning/AI-powered language learning tools

Immune cells play a fundamental role in health and disease. We are applying the latest molecular and cellular multi-omics analysis platforms (single-cell and spatial omics) and computational methods to deliver insights into immune cell biology across a range of human tissues (e.g. the gut, joint, skin, liver, kidney, bladder, brain and blood) and diseases (including immune-mediated diseases, malignancies and infectious diseases). The insights obtained through these omics analyses will help to facilitate and rationalise target selection, drug development, positioning and repurposing strategies, and hence precision medicine across diseases.

The successful applicant will make use of available and emerging single-cell and spatially-resolved multi-omic datasets (that capture the transcriptome, the cell-surface proteome, the T- and B-cell receptor repertoires and the epigenome) to investigate pathophysiological inflammatory pathways and mechanisms across diseases and over time (e.g. before and after drug treatment). In addition to performing analyses with available pipelines and tools (e.g. Panpipes, COMPASS), the applicant will have the opportunity to develop and apply generative machine learning (ML) approaches to better encapsulate the relationships between genes, enabling the investigation of regulatory gene network perturbations or other subtle behaviour that is not easily identifiable with standard data analyses.

The student will also be involved in developing and contributing to a platform for the user-friendly visualization of high-resolution metabolic data, including the incorporation of AI-powered language learning tools. Depending on student interests, a wet-lab component can be incorporated into the project with respect to tissue profiling by spatial transcriptomics, hyperplexed imaging and/or biochemical profiling (at Diamond Light Source), or experimental validation.

KEYWORDS

Immunology, single-cell, spatial transcriptomics, machine learning, artificial intelligence

TRAINING OPPORTUNITIES

The Kennedy Institute of Rheumatology is a world-class research centre, located in the University of Oxford’s Old Road campus, housing basic and clinical scientists and bioinformatics working on immunology and inflammation. This project will combine state-of-the-art omics, bioinformatics, and ML/AI approaches and the student will receive regular training and mentoring with respect to immunology and computational biology.

The student will join a vibrant postgraduate community at the Kennedy, and will benefit from attending seminars delivered by world-leading scientists in the department and across the University, from public engagement opportunities and from transferable skills and other training sessions. The student will present their work at group meetings and national and international conferences.

KEY PUBLICATIONS

Curion F, et al. (2024) Panpipes: Pipelines for multimodal single-cell and spatial transcriptomic data analysis. Genome Biology https://genomebiology.biomedcentral.com/articles/10.1186/s13059-024-03322-7; https://github.com/DendrouLab/panpipes; https://panpipes-pipelines.readthedocs.io/en/latest/

Thomas T, et al. (2023) A longitudinal single-cell therapeutic atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease. bioRxiv https://doi.org/10.1101/2023.05.05.539635

Grant-Peters M, et al. (2022) Biochemical and metabolic maladaptation underpins pathological niches in progressive multiple sclerosis. bioRxiv https://doi.org/10.1101/2022.09.26.509462

Cui H, et al. (2023) scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI. bioRxiv https://doi.org/10.1101/2023.04.30.538439

Weeratunga P, et al. (2023) Unbiased single cell spatial analysis localises inflammatory clusters of immature neutrophils-CD8 T cells to alveolar progenitor cells in fatal COVID-19 lungs. medRxiv https://doi.org/10.1101/2022.12.21.22283654; https://mdv.molbiol.ox.ac.uk/ 

THEMES

Inflammation

Computational biology

Machine learning

Clinical pathology 

CONTACT INFORMATION OF ALL SUPERVISORS

calliope.dendrou@kennedy.ox.ac.uk

dan.woodcock@nds.ox.ac.uk

stephen.taylor@well.ox.ac.uk

The Kennedy Institute is a proud supporter of the Academic Futures scholarship programme, designed to address under-representation and help improve equality, diversity and inclusion in our graduate student body.  The Kennedy and the wider University rely on bringing the very best minds from across the world together, whatever their race, gender, religion or background to create new ideas, insights and innovations to change the world for the better. Up to 50 full awards are available across the three programme streams, and you can find further information on each stream on their individual tabs (Academic futures | Graduate access | University of Oxford).

How to Apply

Please contact the relevant supervisor(s), to register your interest in the project, and the departmental Education Team (graduate.studies@ndorms.ox.ac.uk), who will be able to advise you of the essential requirements for the programme and provide further information on how to make an official application.

Interested applicants should have, or expect to obtain, a first or upper second-class BSc degree or equivalent in a relevant subject and will also need to provide evidence of English language competence (where applicable). The application guide and form is found online and the DPhil or MSc by research will commence in October 2025.

Applications should be made to the following programme using the specified course code.

D.Phil in Molecular and Cellular Medicine (course code: RD_MP1)

For further information, please visit http://www.ox.ac.uk/admissions/graduate/applying-to-oxford.

Interviews to be held week commencing 13th January 2025.