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will deliver projects that leverage large-scale electronic health record data and rich cytometry data derived from full blood count analysers to develop and refine machine learning models to improved
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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53 Faculty of Earth Sciences, Geography and Astronomy Startdate: 01.10.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.09.2031 Reference
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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of research projects on human immunity against bacterial and viral infections using human challenge models. You will support the research of Post-Doctoral Scientists, whilst obtaining training in working
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The Opportunity: We are seeking a post-doctoral fellow to develop ‘genome surgery’ approaches to correct patient-modelled variants in cell-based and in vivo models as part of our recently launched
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the cellular and molecular mechanisms driving tumour development. In this role, you will support a team of scientists using genetically engineered mouse models (GEMMs) and transplantable tumour models (e.g
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postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide an exceptional launchpad