509 algorithm-phd-"Prof"-"Washington-University-in-St"-"Prof" Fellowship positions in United Kingdom
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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river system Develop, test and apply algorithms for the processing and analysis of satellite data drawing on the latest physics-based and/or data-driven techniques Contribute to work on the automation and
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progression once in post to £48,149 Grade: 7 Full Time, Fixed Term contract up to March 2028 Closing date: 13th August 2025 Background This research project aims to establish the theoretical and algorithmic
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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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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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applications for monitoring and managing aquatic environments under study, the Mekong river delta and the Forth river system Develop, test and apply algorithms for the processing and analysis of satellite data
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to be agreed with the successful candidate. We invite applications for a Postdoctoral Research Associate to join the OCEAN project (On intelligenCE And Networks: Mathematical and Algorithmic Foundations
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark