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productivity and output • Learn and be fully independent on the existing laboratory workflows, such as transcriptomics analytical pipelines running on Python such as Topometry • Manage own academic
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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learning and working environment. ABOUT THE ROLE This role offers an exciting opportunity to contribute to the delivery and development of teaching across Finance, Financial Technology and Trading at both
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support the University’s Health and Safety Policy. To be confident and able to use and instruct on Domestic and Dubied knit machines, and linkers, to produce garments and knit swatches to a high standard
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on sourcing and assessing candidates within defined timeframes. One week, you might be talent pooling for Technicians; the next, you could be recruiting for a Lecturer in Machine Learning. This role will allow
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the Photonic Quantum Information group (PQI) led by Professor Ian Walmsley in the area of quantum machine learning. You will engage in advanced study and academic research, working to develop and carry out
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for this vacancy they may be eligible for a bonus. Please ensure when applying, that you select ‘other’ and note their name when answering the question ‘Where did you learn of this job?'. The referrer must be noted
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contributory pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning