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vision, XR and generative models, specifically for capturing challenging scenarios and training deep learning systems to create better experiences for human users and learners. You will contribute
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy infrastructure. The research will investigate how machine learning
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see
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infrastructure. The research will investigate how machine learning models can be designed and deployed efficiently on constrained hardware platforms while supporting the reliability and security requirements
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testing and condition monitoring using modern machine learning, including multimodal foundation models and related data-driven and physics-informed approaches. Research topics may include visual and real
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-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and intelligent transport. International evaluations place DESS in
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Engineering, Science and Systems (DESS) research group focuses on data-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
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At the Faculty of Medicine, Department of Health Science and Technology, a position as Assistant Professor in Tongue computer interfacing for computers and roboticsis open for appointment from June