22 machine-learning "https:" "https:" "https:" "https:" uni jobs at KINGS COLLEGE LONDON
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of Mental Health & Psychological Sciences, and our NHS and industry partners. We particularly welcome candidates whose expertise complements existing departmental strengths in machine learning, multimodal
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large-scale speech and wearable data from participants in the GLAD Study cohort (https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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complements existing departmental strengths in machine learning, multimodal data integration, digital phenotyping, and trial emulation using electronic health records. This is a full-time post (35 hours per
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system may hold clues to how psychosis and other psychiatric disorders are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine
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communication skills Desirable criteria Experience in application of machine learning to metamaterials modelling Experience in modelling molecular interactions Experience in modelling of mass transport
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of machine learning to metamaterials modelling Experience in modelling molecular interactions Experience in modelling of mass transport at the nanoscale Downloading a copy of our Job Description Full details
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Josip Car Contact Details: josip.car@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/401566/inkfish-senior-rese… Requirements Additional Information Work Location(s
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of a multidisciplinary team Skilled in explaining technical methods to a general audience Desirable criteria Experience with machine learning Coding in PyTorch Evidence of published work simulating
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of education and research for King’s Engineering. We offer undergraduate and postgraduate education, with a distinctive approach, combining traditional teaching methods with modern, project-based learning
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interaction. Within CORE, SAIR focuses on multimodal machine learning for human-centred embodied AI, specifically tackling challenges in multimodal perception, understanding and forecasting human behaviour, as