159 machine-learning-"https:"-"https:"-"https:"-"https:"-"The-Open-University" positions at KINGS COLLEGE LONDON in United Kingdom
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traditional teaching methods with modern, project-based learning, catering for the needs of our students and the industries in which they will work. It is essential that applicants have the enthusiasm and
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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statistical and machine learning techniques to analyse how network activity changes in response to these perturbations. This involves identifying patterns, dependencies, and emergent properties across different
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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environment. Strong computer skills (proficient with MS WORD, Excel and web-based applications). Eye for detail and ability to accurately document findings in written reports. Able to learn and work to SOPs and
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general audience Desirable criteria Experience with machine learning Coding in PyTorch Evidence of published work simulating soft tissue mechanics Experience supervising junior team members and PhD students
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and blended learning across King’s College London. At the same time, you’ll benefit from being part of a creative and experienced team of developers within King’s Digital, working to make Moodle more
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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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global partnerships. With world-renowned researchers and a passionate student body, we are always encouraging innovative and progressive collaboration, as well as new ways to work and learn. Further