13 algorithm-"Multiple"-"Prof"-"Simons-Foundation"-"DIFFER" positions in United Kingdom
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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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for facilitating effective communication with, and interaction between, the Hub’s various stakeholders, both internal and external. This will involve managing multiple communications channels and planning, creating
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stakeholders, both internal and external. This will involve managing multiple communications channels and planning, creating and distributing high quality content to promote the Hub’s activities and impact. This
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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network performance across multiple layers and levels of abstraction The ideal candidate will possess strong expertise in quantum communication and networking, with a solid command of both theoretical
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contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to contribute to: Extend our software platforms for electronic healthcare record
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at the interface between computational design and in vitro experiments, the team has developed multiple in silico and in vitro methods to design novel antibodies and nanobodies as therapeutic agents and research
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals