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Senior Bioinformatician in Single-cell/Spatial Multi-omics and Machine Learning/Artificial Intellige

University of Oxford

Oxford

On-site

GBP 49,000 - 59,000

Full time

Today
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Job summary

A prestigious university in the United Kingdom is seeking a Senior Bioinformatician to lead the management and analysis of large-scale datasets within the Nuffield Department. You will develop computational pipelines for single-cell and spatial omics analysis while collaborating with industry and clinical partners. The ideal candidate holds a PhD with expertise in bioinformatics and machine learning, showcasing strong Python skills. This is a full-time three-year position offering a salary of £49,119-£58,265.

Qualifications

  • PhD/DPhil with a significant computational and/or statistical element, or comparable industrial research experience.
  • Expertise in bioinformatics analysis of omics datasets, including single-cell and spatial multi-omics.
  • Experience applying machine learning/AI methods and strong knowledge of Python programming.

Responsibilities

  • Develop new methodologies and maintain computational pipelines for integration of omics data.
  • Collaborate with experimental, clinical, and industry partners.
  • Provide bioinformatics input into grant proposals.

Skills

Bioinformatics analysis of omics datasets
Machine learning/AI methods
Python programming
Collaborative work with experimental partners

Education

PhD/DPhil with significant computational/statistical element

Tools

R
Job description
Senior Bioinformatician in Single-cell/Spatial Multi-omics and Machine Learning/Artificial Intelligence

Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS)

Grade 8: Salary in the range of £49,119-£58,265 per annum.

This is a fixed‑term, full‑time position for 3 years, in the first instance.

Overview

We are looking for a Senior Bioinformatician in Single-cell/Spatial Multi-omics and Machine Learning/Artificial Intelligence to join the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford. The Experimental Medicine Collaboration (EMC) will combine GSK’s drug discovery, target validation and clinical development with Oxford’s expertise in developing new drug therapies and its Experimental Medicine Clinical Research Facility (EMCRF) at Old Road Campus.

The post‑holder will lead the management and analysis of large‑scale datasets to address joint GSK‑Oxford hypotheses, working with academic, clinical and industry colleagues. They will help to develop and maintain computational pipelines and workflows for single‑cell and spatial omics analysis and integration with clinical, demographic and experimental data. Implementation and/or development of ML/AI approaches to address key questions is also highly encouraged.

Key Responsibilities
  • Develop new methodologies and take overall or shared responsibility for the development and maintenance of computational pipelines for integration of omics data with other relevant datasets.
  • Collaborate with experimental, clinical and industry partners to better understand the domain, address scientific hypotheses and support programme objectives.
  • Provide bioinformatics input into outline and full grant proposals, acting as a co‑applicant.
Qualifications
  • PhD/DPhil with a significant computational and/or statistical element, or comparable industrial research experience.
  • Expertise in bioinformatics analysis of omics datasets, including single‑cell and spatial multi‑omics, and single‑cell immune repertoire analysis.
  • Experience applying machine learning/AI methods and strong knowledge of Python programming.
  • Desirable: experience and knowledge of another relevant programming language (e.g. R) and experience developing computational methods for omics data analysis.
Additional Information
  • Security pre‑employment checks required: satisfactory basic Disclosure and Barring Service check.
  • Closing date for this position is 12 noon on 22 December 2025.
  • Contact email for applications: recruitment@ndorms.ox.ac.uk
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