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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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, predictive maintenance algorithms, and digital twin technologies tailored specifically for healthcare, aviation, and sanitation industries. You will identify critical operational pain points within
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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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new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number of awards
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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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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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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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debugging and profiling Parallel numerical algorithms and libraries System software stack administration and novel/experimental hardware. Over the course of the appointment, the candidate will be supported
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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organisational and time-management skills, with the ability to manage multiple tasks. The ability to work both independently and as part of a collaborative team, often across disciplines. A demonstrable interest