Postdoctoral research assistant in computational pathology & spatial multiomics

Responsibilities

• Plan, coordinate and deliver high-quality research activities and outputs in collaboration with the Principal Investigator and project partners.
• Design and test scientific hypotheses, analyse complex multimodal datasets and interpret findings.
• Develop computational and bioinformatics pipelines for spatial transcriptomics, multiomics and imaging data.
• Integrate tissue imaging, molecular and clinical datasets to generate advanced disease models.
• Contribute to the preparation of manuscripts for publication in leading international journals.
• Present research findings at group meetings and national and international conferences.
• Collaborate effectively with researchers across the 3DxN consortium, including international partners.
• Provide technical guidance and mentorship to research students and technical staff where appropriate.

Qualifications

Applicants should hold, or be close to completion of, a PhD/DPhil in a relevant discipline such as bioinformatics, computer science, applied mathematics, computational biology or a related field.

• Strong programming skills in Python and R.
• Experience developing bioinformatics and/or AI/ML analysis pipelines for spatial transcriptomics, proteomics or single-cell genomics data.
• Excellent analytical, problem-solving and communication skills.
• The ability to work independently and collaboratively within a multidisciplinary research environment.

Experience with spatial transcriptomics, multiplexed imaging, tissue pathology or blood cancer research would be advantageous.

Program Overview

Nuffield Division of Clinical Laboratory Sciences, John Radcliffe Hospital, Oxford, OX3 9DU. Applicants are invited for a PDRA position at the Nuffield Division of Clinical Laboratory Sciences (Radcliffe Department of Medicine) - University of Oxford to participate in a major new multidisciplinary bioimaging programme, 3DxN. Background: Ageing and disease are accompanied by changes in the appearance of tissues and cellular microenvironments. Current clinical pathology relies largely on classification and grading systems that do not fully capture the molecular and cellular basis of health and disease. This post forms part of the Wellcome-funded 3DxN consortium, bringing together researchers from the University of Oxford and the University of Cape Town. The programme integrates AI-driven image analysis with molecular and clinical data to identify novel disease-associated features and translate them into clinically deployable diagnostic and prognostic tools. The successful candidate will contribute to the development of a spatially resolved 3D atlas of the bone marrow, advancing precision diagnostics in blood cancer and skeletal injury through the integration of advanced imaging, spatial transcriptomics and computational pathology.

Role

The postholder will join the Spatial and Translational Pathology Group and analyse bone biopsy samples using 2D and 3D tissue imaging and spatial transcriptomics technologies. They will develop and apply computational methods to integrate imaging, molecular and clinical datasets, generating new insights into bone marrow biology, blood cancer and skeletal disease. The role offers opportunities to collaborate with leading clinician scientists, biomedical engineers and computational researchers, and to further develop expertise in AI, machine learning, data integration and advanced bioimage analysis.