545 parallel-computing-numerical-methods-"Prof" Postdoctoral positions in United Kingdom
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annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting The Department of Computer Science seeks to employ
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joint initiative of King’s College London (Prof. Mauro Giacca), University of Oxford (Prof. Paul Riley and Prof. Robin Choudhury), and University of Edinburgh (Prof. Andrew Baker). This project will
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Formstone (see Panousopoulou et al. J. Cell Sci. 2016 (https://doi.org/10.1242/jcs.180703) and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https://doi: 10.1038/ncomms11469 and Prof. Philippa
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a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification
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a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification
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therapies to stimulate heart repair and regeneration in patients with heart failure, for which there are currently no effective treatments. REACT is a joint initiative of King’s College London (Prof. Mauro
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, model predictive control, parallel computing using JAX and rapid online learning, is highly desirable, but candidates demonstrating an ability and willingness to become familiar with these topics and able
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research teams led by Prof Knight, and Prof Screen working collaboratively at Queen Mary. The PDRA will interact with a team of academics, PDRAs, and PhD students, working on related organ-chip models, as
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design
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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris