49 algorithm-development-"Multiple"-"Prof"-"Simons-Foundation"-"St" positions at University of Exeter
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PhD Studentship: Subcortical brain development and disorders, funded PhD at the University of Exeter
and coordinate motor responses. Despite its importance, our understanding of its development and how it may be disrupted in neurodevelopmental disorders is still largely unknown. This funded PhD project
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Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about
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observations – to develop statistical tools that integrate multiple data streams into indicators of individual health. The project will interface directly with management agencies (NOAA, WDFW, DFO), and the
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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be given sector-leading training and development with outstanding facilities and resources. The EPSRC studentships will be offered across the whole of EPSRC’s remit , with projects at the interface
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Project details Objective: This project aims to develop a wireless, nanoengineered graphene-based biosensor for real-time dopamine (DA) detection. The wireless design of the sensor aims to enable
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functions). Explore model-based RL approaches that integrate learned models with planning and adaptation mechanisms. Hybrid Evolutionary-RL Framework Develop novel frameworks with evolutionary algorithms
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functions). Explore model-based RL approaches that integrate learned models with planning and adaptation mechanisms. Hybrid Evolutionary-RL Framework Develop novel frameworks with evolutionary algorithms
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predictive performance, computational efficiency, and spatial resolution through algorithm optimisation, tuning, and refined covariates. Assess trade-offs between spatial resolution and other performance
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person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As