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including the following: Use of Machine Learning; Web applications; Exploiting the capabilities of the University’s High Performance Computing facilities particularly in data-intensive applications. The post
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or more of these technologies: ◦ Shared and distributed memory programming tools) (e.g. OpenMP, MPI, CUDA) ◦ Make and other build and installation management tools ◦ Machine learning
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. Candidates with strong track records in computational tropical geometry, non-archimedean analysis and geometry, machine learning, and related areas are encouraged to apply. Hybrid and flex working arrangements
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applicants with expertise in the fields of artificial intelligence, computer vision, edge computing, digital twins, human-computer interaction, user modelling, robotics, resilient computing, where
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research, delivering tutorials or computer practical classes, and possibly some lecturing. Allocation of teaching duties will take account of the Fellow’s expertise and experience as well as the Department’s
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including robotics, human computer interaction, data visualisation and computer graphics including those with strong links to related work in neural computation and deep machine learning. The applicant will
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within their role. Person Specification Applicants must demonstrate research excellence in the field of Power Electronics, Machines and Drives, with the ability to teach our students to an exceptional
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-Computer Interaction (HCI), Software Engineering (SE), and Technology-enhanced Learning (TEL). All themes share the core goal to promote AI for social good by working on real-world problems and having
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in one or more of the Control Engineering specialisations including, but not limited to, Systems Modelling and Prediction for Electronics and Communications, Machine / Deep Learning for / in Control
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of advanced energy storage solutions and integration into the smart grid ecosystem. Implementation of machine learning techniques for predictive maintenance and fault detection in power systems. Exploration