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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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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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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
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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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work with in vitro and in vivo models of genetic diseases would be advantageous. Please see the below 'Job Description' for further details on the role, responsibilities, and selection criteria, as
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candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities
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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 characterisation of in vivo models of myeloid neoplasms and
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will 1) develop a hydrofibre based dressing loaded with AMP and perform confirmatory spectrum-of-efficacy studies using established wound models; and 2) compile a robust regulatory package including in
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and skills of the successful applicant. Access to high-performance computing facilities and cloud-based quantum hardware will be provided to support simulation and verification of theoretical methods