Postdoctoral Researcher in Renal Pathology

University of Oxford; Oxford; On-site; GBP 39,000 - 48,000; Full time

Job summary

University of Oxford is seeking a Postdoctoral Researcher to join the Clinical Proteomics Group and Kidney Pathology Group in Oxford to investigate focal segmental glomerulosclerosis (FSGS). You will work with multi-omic and clinical data to identify molecular signatures and immune mechanisms, and contribute to publications and collaborative projects.

The role combines experimental and computational work, using LC-MS and spatial proteomics to advance understanding of kidney disease, with a

Qualifications

• PhD/DPhil in proteomics, biomedical science or bioinformatics required.
• Hands-on experience in renal pathology research, including mouse and cell line models, and tissue processing/histology.
• Experience in spatial/single-cell LC-MS proteomics and transcriptomics is essential.
• Experience operating LC-MS and supporting equipment (timsTOF, Leica LMD7, cellenONE).

Responsibilities

• Integrate multi-omic and clinical datasets to identify molecular profiles linked to patient phenotypes and outcomes.
• Contribute to spatial proteomic analyses of human kidney samples and validate findings in vitro and in vivo.
• Develop and adapt experimental approaches; analyse complex data and contribute to publications and collaborations.

Skills

Omics data generation

Computational analysis

Renal pathology experience

Mouse models

Cell line models

Education

PhD/ DPhil in proteomics or biomedical or bioinformatics

Tools

LC-MS

timsTOF

Leica LMD7

cellenONE

Job description

Postdoctoral Researcher in Renal Pathology

Centre for Medicines Discovery, NDM Research Building, Old Road Campus, Headington, Oxford, OX3 7FZ

We are seeking a motivated Postdoctoral Researcher to join the Clinical Proteomics Group and Kidney Pathology Group to investigate focal segmental glomerulosclerosis (FSGS), a progressive kidney disease that can lead to kidney failure. The project aims to identify clinically relevant molecular signatures of FSGS and improve understanding of the immunological mechanisms driving the disease, with the potential to inform new therapeutic approaches.

You will integrate multi-omic and clinical datasets to identify molecular profiles associated with patient phenotypes and outcomes, while contributing to spatial proteomic analysis of human kidney samples. You will validate findings using in vitro and in vivo models, develop and adapt experimental approaches, analyse complex scientific data, and contribute to publications, presentations and collaborative research projects.

You will have experience in omics data generation and computational analysis and be comfortable working across both laboratory and bioinformatics research. You will join a supportive multidisciplinary team where you can further develop these skills, making this an excellent opportunity for a researcher keen to combine experimental and computational approaches to address an important clinical challenge in kidney disease.

It is essential that you hold a PhD/DPhil (or close to completion) in proteomics, biomedical, bioinformatics or other relevant subjects. You must have hands-on experience in renal pathology research, including using mouse and cell line models, and kidney tissue processing and histology. Experience in spatial/single-cell LC-MS proteomics and transcriptomics is a must. It is essential that you have experience in operating LC-MS and supporting equipments (timsTOF, Leica LMD7, cellenONE).

This position is offered full time on a fixed term contract until 31 December 2027 and is funded by the department. Only applications received before 12 midday on Tuesday 10 November 2026 will be considered.

Pay Scale: RESEARCH GRADE 7

Salary (£): Research Grade 7: Salary in range £39,424-£47,779 per annum (pro rata). This is inclusive of a pensionable Oxford University Weighting of £1,730 per year (pro rata)

Tagged as: Life Sciences

Contact Person: Kristina Limbu

Vacancy ID: 189323

Contact Phone: 10-Nov-2026 12:00

Contact Email: [e-mail]