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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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BMS constraints. Experience with system identification, uncertainty-aware modelling, large datasets, and machine learning. Evidence of research capability through a thesis, publications, conference
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research in machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community. To provide guidance and support to any
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engineers through PhD and postdoctoral supervision. Key responsibilities include: Establishing and leading an internationally recognised research programme in computer engineering in one or more of: (i
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education, an ability and willingness to teach at all levels of the program, and a PhD in operations research, mathematics, statistics, or a related field by the start of the appointment. Salary will be
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and
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Data Analytics, including but not limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks
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intelligence and machine learning, with areas such as enzyme discovery and engineering, metabolic pathway design, genetic-code engineering, protein engineering, and the biosynthesis or biological incorporation
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this PhD project, you will build a self-driving laboratory platform that will help solving outstanding questions at the forefront of (photo)chemistry by implementing automated spectroscopy workflows