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the problem of induction”. How biological and artificial agents can use limited evidence to effectively learn and generalise is a long standing issue for psychology, AI/computational sciences, neuroscience and
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for better evaluation of LLMs for real world scenarios, both reference-free and benchmark-based evaluation, augmenting LLMs with temporal reasoning and the ability to perform longitudinal predictions with
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, with particular emphasis on bio-based composite materials, to simulate the processes of water absorption and damage propagation. You will contribute to the success of the research project through close
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opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, and flexible working arrangements. The post is based at the Mile End Campus in London. It is a
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materials-based heterostructures , where the 2D nanosheets will act as transducers for electrical sensing applications. This will generate a knowledge-based platform to allow us to rationally engineer 2D
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of this study will have significant potential for advancing the clinical impact of hiPSC-based therapies. About You We seek outstanding, self-motivated, and ambitious junior researchers committed to pursuing a
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uncertainty. Relevant areas include interpretable probabilistic, causal, Bayesian, and knowledge-based networks. While expertise in electromagnetics is not essential, applicants must be willing to broaden
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(inclusive of London Weighting) based on experience. The successful candidate will be part of the new Centre for Vaccinology and Regenerative Medicine, based on the Hawkshead Campus of the RVC (https
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Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of Eyesight testing. Free parking The post is based in Egham, Surrey where the College is situated in a beautiful, leafy
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candidate with an interest in flight mechanics and sensory systems. The post will be based on site at our state-of-the-art laboratory, with some flexible working available by arrangement. We offer a generous