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considered. General interest in responsible AI, coursework, use of machine-learning tools, unpublished projects, or publications only in unrelated venues do not satisfy this requirement. For collaborative
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into mechanistic insight Lead a PhD student in development of a controlled flow system for in situ ATR-UV–Vis spectroscopy including polarization and use it to monitor the formation, orientation, and evolution
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school, and taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a
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of further research funding. If appropriate, the role may involve acting as a formal co-supervisor for research students. The post holders will hold a relevant PhD/DPhil, or be near completion, in Statistics
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machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational performance while enabling more
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that affects the measured data and translate the observations into mechanistic insight Lead a PhD student in development of a controlled flow system for in situ ATR-UV–Vis spectroscopy including
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Type of Position Staff Position Time Status Full-Time Required Education PhD Required Related Experience None Required License/Registration/Certification None Physical Requirements Standing for long
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Type of Position Staff Position Time Status Full-Time Required Education PhD Required Related Experience None Required License/Registration/Certification None Physical Requirements Standing for long
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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, a BA, BS, and MS in Chemistry including biochemistry options, and a PhD in Medicinal Biochemistry. Our department is housed in a 170,000 square foot, $35 million state of the art science building