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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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, defensive mechanisms and related topics to the safe deployment of systems contain multiple LLM and VLM powered models. You will be responsible for Developing and implementing; capability evaluations, attacks
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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of the correctness of software and hardware systems using machine learning. Recent advances in neural certificates—such as neural model checking and neural termination analysis—have shown promising results in
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of developing a knowledge cluster as a model for transition around the UK and internationally. This will build on the network and findings developed in an existing workshop series that brings together farmers
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Institute). The position is fixed term for 36 months and will provide opportunities to work on aircraft icing modelling and experimental campaigns. Ice crystal icing is one of the least well characterised
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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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, such as sedimentation, meltwater flow, and vegetation change, into active drivers of adaptive design. This interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and
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research to investigate the molecular circuits that regulate immune cell function in models of disease. The work will build on our recent breakthroughs and involve techniques such as CRISPR-screens, single
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are working to set up a new,human challenge model ofStaphylococcus aureus skin infection. This model will be used to study the early interactions between the human immune system and invading bacteria. From