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successful in this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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an exciting opportunity to a graduate with the relevant skills and knowledge to develop and implement machine learning techniques to derive new-to-sector advanced insights from Aids to Navigation maintenance
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assessments (EMA), and passively monitored behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning
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behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning, experimental psychology, audiology, cognitive
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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understanding of: Signal processing algorithms, Security and Privacy Antennas and RF sensing Machine learning for communications systems Integrated Sensing and Communications You will enjoy adventure in research
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an international reputation in AI and Machine Learning, Cyber Security, 5G and Next Generation Communication Systems and Advanced Materials Innovation. The teaching is organised at a School level and you will join
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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, Recommender Systems, Machine Learning or Artificial Intelligence (applied to text or financial data) A3 A comprehensive and up-to-date knowledge of the wider subject area or subject specialism in Information