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Field
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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Join our multidisciplinary research team to develop and apply machine learning and bioinformatic algorithms in biomedical research. This PhD project will focus on developing machine learning
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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reinforcement learning and evolutionary algorithms to balance emissions reduction, safety, commuter convenience, economic factors and policy evaluation to generate optimised sustainable mobility plans. Decision