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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate
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Rationale: Flooding – the most wide-spread natural hazard – affects every country and region of the world. Flood risk is expected to increase due to climate change, as evidenced by recent recurring
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Professor Akane Kawamura Akane.Kawamura@newcastle.ac.uk For more information on the School of Natural and Environmental Sciences, please click here . To apply, please complete the online application and
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Psychology and Clinical Language Sciences (PCLS) and Food and Nutritional Sciences (FNS). Eligibility: Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent in Psychology
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Flooding stands as the most prevalent natural hazard. However, whilst substantial research effort has been reported in the last decade to develop high-performance physics-based models for more
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(bbs24@cam.ac.uk ) for queries of a technical nature related to the role or csic-admin@eng.cam.ac.uk for queries related to the application process. Please quote reference NM45544 on your application and
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contact Dr Brian Sheil (bbs24@cam.ac.uk ) for queries of a technical nature related to the role or csic-admin@eng.cam.ac.uk for queries related to the application process. Please quote reference NM45544
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area. Significant experience in graphic software development and highly proficient in computer programming languages for XR development. Proven ability to translate and implement specialised innovative ideas
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also exploit machine-learning techniques to train more approximate simulation methods with highly accurate reference DFT results. This will allow simulation of system sizes that are difficult to treat
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ability, and a fluent spoken English is needed in this work. What we offer? This position is foreseen to run from Spring 2025 onward, but the start date is partially negotiable. The position will be filled