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evaluations, attacks 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
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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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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the Cheerambathur Lab on the novel roles of kinetochore proteins in brain development and explores how the chromosome segregation machinery is reutilized in post-mitotic neurons to construct and repair neural
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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About the Role Applications are invited for a full-time Postdoctoral Research Assistant to investigate mechanical sensing and mechanical memory in cardiac muscle cells and its involvement in