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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme, focused on understanding and preventing disease progression in
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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experience: Essential criteria PhD in computer science, AI or related area Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS
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researcher to investigate the neural mechanisms underlying decision-making, using the fruit fly Drosophila melanogaster as a model system. Funded by the BBSRC, this project will combine innovative behavioural
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computational modelling using artificial neural networks. It brings together teams led by Mohamady El-Gaby (Oxford Experimental Psychology), Matthew Nour (Oxford Psychiatry), Rick Adams (UCL), and Maria Eckstein
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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. Keith Channon – a 5 year renewable award that underpins the work of the group. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of
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emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused on learning and improving how computing, workflows
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largest protein/peptide mimotope dataset foundational for advancing any peptide-based drug discovery programme. The ERC PoC PepVerse project focuses on increasing the technology readiness of this platform
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, state-of-the-art laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About the role We are looking for a highly motivated