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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems
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Applications are invited for the following position: Title of Post: Research Assistant in ADAS Systems JOB SYNOPSIS The successful candidate will undertake the development datasets, machine learning
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machine-learning models to investigate how brain, environment and social factors influence cognition, ageing and neurodegenerative disease. The role will contribute primarily to WP6 and related analytical
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the Teaching and Learning IT Team, overseeing software deployment and system administration for computer labs and BYOD environments in E3LF, and secondarily across campus and remotely. They will manage and
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and Employability Service (CES), within Student Skills and Success in the Office of Students and Learning, is seeking a motivated, collaborative and proactive Employability and Skill Development
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concepts from nonlinear system identification, optimisation, computational complexity, and data-driven modelling, with the long-term objective of extending these ideas to modern AI and machine learning
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catalysts used in chemical processes. The successful candidate will combine state-of-the-art quantum chemical modelling alongside machine learning techniques and contribute to the development of predictive
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collaborative learning. The ideal candidate will demonstrate a commitment to excellence in teaching and research, the ability to embrace delivery in both blended and residential academic pathways, and strong
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University’s Strategic Plan. Key functions of this role include supporting the set up and roll out of a new Learning Management System (LMS); rolling out new development supports associated with the Competency
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the set up and roll out of a new Learning Management System (LMS); rolling out new development supports associated with the Competency Framework; co-ordinating career development supports and outputs from