14 condition-monitoring-machine-learning Postdoctoral positions at KINGS COLLEGE LONDON in Uk
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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support needs of minoritised ethnic people with multiple long-term conditions, and transform how healthcare providers, communities and policymakers construct, respond to, and support them in local 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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projects and publications from the group can be found here: https://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning
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About us The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, and machine learning. Topics
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become Research Associate and the salary will increase to Grade 6. Desirable criteria Experience in working under BSL3 conditions Experience in handling and the molecular manipulation of SARS-CoV-2
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on advancing outcomes of preventive approaches by understanding what works (and doesn’t) for preventing common mental health conditions in children and young people. In 2026, the department will be based in