30 machine-learning "https:" "https:" "https:" "https:" positions at KINGS COLLEGE LONDON in United Kingdom
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About us The Department of Informatics is looking to appoint a Reader in Computer Vision Education. This is an exciting time to join us as we continue to grow our department and realise our vision
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forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a broad perspective. Faculty members regularly publish in and serve on the program
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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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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
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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