979 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs in United Kingdom
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should also have an interest in data science, machine learning tools or artificial intelligence as applied to biological systems related to immune therapy of cancer. The postholder should be committed
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denotational semantics, abstract machines, as well as string diagrams and graph rewriting. Some knowledge of category theory would be useful but not essential. Being able to formalise the frameworks and
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CANDIDATES ONLY About Us The applicant will join the Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. We are a highly collaborative
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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in theory of probability and statistics, machine learning, or formal methods. The post is available from 2 March 2026 until 1 March 2028. If you are still awaiting your PhD to be awarded you will be
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are committed to maintaining a safe and secure environment for our students, staff, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant
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are committed to maintaining a safe and secure environment for our students, staff, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant
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with machine learning or image analysis. An interest in environmental sustainability or biodiversity conservation is highly desirable. Main duties and responsibilities Build and train initial AI models
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execution while also developing a long-term forecasting model using machine learning algorithms (prior experience with Machine Learning model implementation would be advantageous here). You will also have the
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well as companies and governmental organisations . They will contribute to the activities of the wider machine learning and data science research group and write up the results of their work, with co-authors