109 algorithm-"Multiple"-"U"-"Prof" "NTNU Norwegian University of Science and Technology" Fellowship positions in United Kingdom
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Role type : Continuing; 0.8 to 1 FTE (negotiable) Faculty : Faculty of Medicine, Dentistry & Health Sciences Department/School : Collaborative Centre for Genomic Cancer Medicine Salary : Level C - $149,701.00 - 172,613.00 p.a. plus 17% super Lead groundbreaking cancer genomics research /...
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We are now recruiting 2 full time Research Fellows to work with Stephen Farrall and colleagues at Warwick (Emily Gray) and Queen Mary College, University of London (Maria Grasso) on their research into politics and crime. The research is funded by the Leverhulme Trust. The School and the...
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Dependent type theory is a foundation of mathematics that allows us to mechanise arguments, and is closely related to higher category theory. It serves as that basis of programming languages and proof assistants. The current project aims to make progress in the field of dependent type theory...
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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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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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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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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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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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It