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experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools; Code synthesis
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research assistants. They will be supported to develop their own research ideas and apply for personal fellowships. About You The ideal candidate will hold (or near completion of) a PhD/DPhil in
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academics working on biogeochemistry in the Department. About you You will hold, or be close to completion of, a relevant PhD/DPhil, together with relevant experience. You will possess sufficient specialist
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will be required due to regulated activity involving children and ‘at risk’ adults. The successful candidate will hold, or have submitted a relevant PhD/DPhil (or equivalent) in a relevant discipline
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; testing hypotheses and analyzing data from a variety of sources, reviewing and refining working hypotheses as appropriate; engage with industrial stakeholders to understand needs and disseminate results
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on process development, electrode manufacture and performance assessment, but depending on the skills of the successful applicant, may also involve some aspects of modelling or data science. The post is funded
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to implantation, including validating methods in virtual in vivo environments. • Collaborate with engineers to refine fuel cell specifications and support in vivo experiments. You should hold a relevant PhD
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data from patient samples, including DNA methylation, histone modifications, single-cell transcriptomics and chromatin accessibility. You will contribute to the study and sequencing design, collaborate
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evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
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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