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Field
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implementation of position location estimation using Machine Learning (ML) techniques has been proposed as a methodology to improve performance beyond that of existing techniques, particularly in non-line-of-sight
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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The project: An exciting opportunity is available for a talented and motivated PhD candidate to pursue cutting-edge research on applying generative artificial intelligence and reinforcement learning
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. Nowadays AI and Machine Learning techniques achieve impressive detection performance for these sensors, however they are most useful in unobstructed areas (e.g. highway) within direct line-of-sight, and
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description The project is about development of systems for gasification of different types of biomass such as waste and sludge. Focus in the PhD work is on modelling, simulation and optimization of processes
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applicants should contact Professor Chris Murgatroyd for an informal discussion. To apply you will need to complete the online application form for a full-time PhD in Life Sciences (or download the PGR
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computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as
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developments in artificial intelligence (AI), machine learning (ML) and microelectronics have enabled drones to work even more efficiently, enabling them to address emerging demands in several sectors including
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Innovation Inclusiveness Learning Environments Quality Teaching Workforce Development Research will help inform and impact education policy and practices within the state. Recipients of this prestigious
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Embark on a thrilling, fully funded four-year PhD journey, with an enhanced stipend of £24,000 per year, and deliver new evidence on how nature-based solutions can reduce the occurrence and mitigate