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Field
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or interest in runtime reconfiguration techniques and system safety considerations. Experience working with machine learning methods for control, perception, or decision-making in physical systems is an
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PhD Studentship in Aeronautics: Real-time machine learning and optimisation for extreme weather (AE0073) Start Date: Between 1 August 2026 and 1 July 2027 Introduction: Climate change is
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machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite missions (e.g., CO2M, TANGO, Sentinel-4/5). Your research will contribute directly to monitoring global efforts
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guarantees. This includes working with techniques such as differential privacy and PAC-privacy to enable safe model and explanation release. Familiarity with privacy-preserving machine learning methods is a
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passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea
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Science Engineering have the opportunity to learn a broad spectrum of methods through laboratory rotation. This can help students gain experience in different research areas and develop new skills that may