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dynamics and (at intermediate redshifts) strong gravitational lensing, thus preserving and extending the team’s lead in this field. Applicants should have a PhD (or close to completion) in (Astro) physics
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institutions in the programme grant and with supporting industrial partners. About you You should possess a university PhD degree in mechanical engineering or a similar discipline, preferably with experience
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weighting The Department of Computer Science seeks to employ a postdoctoral researcher to work on a new project in the area of LLMs/multi-agent systems, under the direction of PI Professor Michael Wooldridge
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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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dynamics and (at intermediate redshifts) strong gravitational lensing, thus preserving and extending the team’s lead in this field. Applicants should have a PhD (or close to completion) in (Astro) physics
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, contributing £50B to GDP and direct employment for >300,000 people in 12,000 companies. This project will collaborate with the REWIRE IKC (Innovation and Knowledge Centre: Transforming Net Zero with Ultrawide
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of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will work
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. The role will also provide the opportunity to learn and develop skills in structure-based drug design. The role is ideal for someone who has, or is about to be awarded, a PhD in structural biology and would
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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 discispline. You
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, quantitative and qualitative data analysis; and working with a network of European collaborators (the EuroWISE collective). Work Package 2 (Analysis and Data Management): The PDRA will be responsible for data