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18th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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computational physics and/or geosciences and a strong interest in machine learning, Earth observation, and numerical modelling for Arctic prediction. The PhD project will develop methods to improve monitoring and
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-Class Environment: Access to a leading research environment specializing in hardware/software for medical wearables, translational endocrinology, and machine learning for medical time-series. Cutting-Edge
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-principles electronic structure calculations Perform materials screening including machine learning to identify promising thermoelectric materials for cooling technology The successful candidate is expected
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work that covers all the major fields in data science and operations research and core topics in machine learning and computer science relevant for a PhD in Data and Decision Sciences. These courses
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analysis and machine learning, to quantify different types of horse behaviour. Stress evaluation will be performed by analysing biomarkers, specifically cortisol concentrations in faecal samples collected
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
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energy applications. You must have experience with data analysis, machine learning, or AI-supported methods applied to engineering or safety problems. PLEASE NOTE: For detailed information about what the
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral