28 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at King's College London
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of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication skills
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of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication skills
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with data linkage and working with routine healthcare data Experience with machine learning or AI applications in healthcare settings Advisory or consultancy experience Understanding of implementation
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of genomic predictors into multivariable and machine-learning prediction models for treatment outcome. Working closely with Professors Breen, Eley and collaborators across psychiatric genetics, clinical
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. The post is offered at a competitive salary (Grade 6, Spine Point 33 on the KCL salary scale), and includes provisions for travel money, computer equipment and academic and leadership training. This is a
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, and human-centred computing. You will join the Vision & Human-Robot Interaction (VHR) Lab, a multidisciplinary research group working at the intersection of robotics, machine learning, and human
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. The post is offered at a competitive salary (Grade 6, Spine Point 33 on the KCL salary scale), and includes provisions for travel money, computer equipment and academic and leadership training. This is a
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: Essential criteria Be enrolled in or hold a first degree in biomedical engineering, robotics, or relevant discipline. Possess sufficient specialist knowledge in computer aided design, systems integration, and
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community across the university. The position offers broad exposure to research governance and ethics activities, with significant scope for learning and professional development. The post holder will act as
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-design workshops, interviews, requirements gathering, data curation/annotation activities, and contribute to the design and evaluation of human–computer interface prototypes through design sprints and