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processes, optimising use of space and resources to enhance student experience and staff productivity across a high-footfall estate. About you You are organised, agile, and thrive in a busy university
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processing from sources such as vehicle telemetry, traffic APIs (e.g. TomTom), GIS, GPS, OpenStreetMap, Ordnance Survey data - including building and managing scalable data pipelines, designing database
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decision processes. Use the CARLA simulation platform to generate DCD-style data in high-risk or ambiguous driving scenarios. Build a proof-of-concept verification pipeline that maps DCD outputs
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Python and familiarity with LLM frameworks. Experience with machine learning, natural language processing, or time-series modelling. A strong interest in applying AI to engineering and energy-system
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administrative processes. Ability to work independently and make sound operational decisions. How to apply Should you wish to apply for this vacancy, please complete the application on the University website, with
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. The Centre for Vision, Speech and Signal Processing (CVSSP) is an International Centre of Excellence for research in Audio-Visual Machine Perception. The Surrey Institute for People Centred AI (PAI) builds
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. The Centre for Vision, Speech and Signal Processing (CVSSP) is an International Centre of Excellence for research in Audio-Visual Machine Perception. The Surrey Institute for People Centred AI (PAI) builds
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scintillators are solution-processable at relatively low temperatures and their radioluminescence can be easily tuneable across the visible spectrum by varying the material stoichiometry. The main objectives
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, process mapping, data analytics, economic modelling, or a useful area of business theory is needed. Previous experience in some of the business and management areas related to the project, which may include
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to their presence during manufacture and storage. The effect of exposing a material to either of these species is likely to affect its onward behaviour, and data on these processes will support predictive modelling