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Postdoctoral Research Assistant in the Interpretation of Spatial Transcriptomics and Proteomics for Colorectal Cancer, Oxford
Client: University of Oxford
Location: Oxford, United Kingdom
Job Category: Other
EU work permit required: Yes
Job Reference: 4d97e7a1fd41
Job Views: 3
Posted: 24.04.2025
Expiry Date: 08.06.2025
Job Description:
Centre for Human Genetics, Building for Genomic Medicine, Old Road Campus, Roosevelt Drive, Headington, Oxford, OX3 7BN. We have an exciting opportunity for a Postdoctoral Research Assistant in the Interpretation of Spatial Transcriptomics and Proteomics for Colorectal Cancer. You will join the GO-PRECISE team at the Nuffield Department of Medicine, University of Oxford. GlaxoSmithKline and Oxford University (GO) launched the PRECISE Alliance (Pre-Cancer Biology and Immunoprevention) in 2024, with the aim of conducting deep exploration of cancer precursors (precancers) to identify their molecular vulnerabilities and developing methods to intercept them. The alliance is led by Professor Sarah Blagden.
You will be responsible for managing your own academic research and administrative activities and adapting existing and developing new research methodologies and materials. You will analyse quantitative data from a variety of sources, particularly from Spatial Transcriptomics and Spatial Proteomics platforms, and collaborate with colleagues from the Mathematical Institute, Centre for Human Genetics, and the GO-PRECISE Alliance. Other duties will include contributing to community activities such as seminars and networking events and developing skills in many areas of computational biological research via independent study and training courses.
It is essential that you hold a PhD/DPhil (or close to completion) in experimental or theoretical biology, bioinformatics, clinical medicine, or a related discipline and have demonstrated ability to analyse and interpret complex multidimensional data. You will have experience of working with biomedical datasets, such as cancer data and/or spatial data, and experience of programming in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be highly desirable.
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