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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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models optimised with evolutionary algorithms to address combinatorial optimisation in model design and the noisy nature of climate data. The Doctoral Researcher will receive on-the-job training in machine
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mission. You will: Help collate data resources relevant to suicide and self-harm. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and
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7th January 2026 Languages English English English The Department of Biology has a vacancy for a PhD Candidate in Plant Evolutionary Ecology: plant-parasite interactions under climate warming Apply
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Machine Learning. Work plan: Review of the state of the art on Evolutionary Algorithms and image tampering detection; Implementation of an evolutionary algorithm for image tampering detection
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) section. The BEE section investigates ecological and evolutionary patterns and processes underpinning biodiversity, scaling from genes to communities and ecosystems, and how these are affected by
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. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and others) compatible with epidemiology. Produce a digital twin for national suicide and
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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range of disciplines, including evolutionary biology, ecology, computational biology, genetics, and comparative genomics. The build-up of biodiversity gradients from spatial diversification dynamics 1