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We are seeking a full-time Postdoctoral Research Assistant in Computer Vision to join the Visual Geometry Group (Central Oxford). The post is funded by ERC and is fixed-term for 1.5 years with a
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project and is fixed-term for two years, with the possibility of extension. The objective of this project is to carry out computer vision and machine learning research in order to be able to translate
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experimental and computational approaches are employed to shine light into key biological processes during the life of parasitic flatworms. Large-scale sequencing datasets (‘omics’) are generated and analyzed
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vivo culture. You will also investigate cGAS-STING signalling, regulation at the endoplasmic reticulum, and T cell phenotypes and trafficking. A key aspect of the role includes bioinformatic analysis
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analyses of viral proteins using AI-based prediction tools will also be integrated to support evolutionary inference. This work lies at the intersection of evolutionary biology, bioinformatics, and data
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research, and/or bioinformatics leading to impactful publications and experiencing in clinical research. Application Process You will be required to upload a CV and Supporting Statement as part of your
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findings, and represent the group at meetings. A working knowledge of bioinformatics is also essential. One or more first-author scientific publications, experience in protein purification and flow cytometry
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bioinformatic analyses and will liaise with researchers investigating other aspects of the channels, including pharmacologists and cell biologists. What We Offer As an employer, we genuinely care about our
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genome/protein analysis pipelines for Mycobacteria genomics and drug target identification. Bioinformatics techniques will include database-driven analyses, quantitative comparative genomics approaches
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mechanism design. The project will involve close collaboration with project teams at Imperial College London, the Edinburgh Parallel Computing Centre (EPCC) and the Luxembourg Institute of Science and