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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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, BRCA2, and PALB2. Through advanced single cell genomics, in vivo modelling, and immune profiling, the team will study early molecular and cellular changes that occur in high-risk breast tissue. The team
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also highly valuable. The successful candidate will be expected to work on estimating dynamic models of medical spending and savings and is expected to publish in high-impact academic journals, and to
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renewable award. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of approaches including targeted genetic murine models, primary cell
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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will be expected to work on estimating dynamic models of medical spending and savings and is expected to publish in high-impact academic journals, and to contribute to the collegial and intellectual life
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human tumour models including organ/tumour perfusion, slice culture and organoids to ensure data is clinically relevant and to inspire the next generation of effective treatments. The post would suit
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the implications of connecting wearable computing devices such as smart glasses to artificial intelligence large language models. The exact contribution of the post-holder will depend on their background and
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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs
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on the ERC project and your own research interests. You will apply state-of-art methods of social network analysis, such as Stochastic Actor-Oriented Models (training will be available). You will produce high