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27 Jun 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply.

27 Jun 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply.

28 Jan 2022: Information Engineering at Cambridge spans the broad areas of control, communications, signal, speech, image and vision processing, machine learning, and computational neuroscience. ... the cellular basis of learning and memory, control of neuronal

3 Jul 2024: We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its ... in Machine Learning,

4M22. Climate Change Mitigation. 4M23. Electricity and Environment (TPE22). 4M24. Computational Statistics and Machine Learning. ... 4G3. Computational Neuroscience. 4G5. Materials and Molecules: Modelling, Simulation and Machine Learning.

describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in

describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in

describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in

describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in

describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in