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these barriers by putting together a world-leading data resource on suicide and self-harm, and powerful machine learning methodologies compatible with epidemiological principles to produce high-quality evidence
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You will receive project-specific training in numerical modelling tools and techniques and in machine learning. Eligibility requirements If you have received a First-class Honours degree, or a 2:1
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. The National Centre for Suicide Prevention and Self-harm Research (NCSR) is tackling these barriers by putting together a world-leading data resource on suicide and self-harm, and powerful machine learning
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quantum mechanical effects are typically too expensive for simulations of disordered systems like liquids. This PhD will develop and deploy the tools needed high-fidelity simulations: machine learned
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change accelerate, we urgently need smart, evidence-based tools to plan, manage, and protect our marine ecosystems. At the forefront of this innovation is machine learning. Its ability to process complex
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation
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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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implement more effective interventions based on up-to-date predictions. The ideal candidate will have foundational knowledge of machine learning and strong self-motivation. You will be supervised by Dr
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both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate