14 algorithm-"Multiple"-"U"-"Simons-Foundation"-"Prof"-"UNIS" positions at KINGS COLLEGE LONDON in United Kingdom
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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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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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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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will be required to take a leading role across multiple projects, with support from other members of the team. Project topics are agreed with the funders in accordance with their priorities. KIS is a KHP
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expertise in organoid models of neurodevelopment to join our team and be involved in a MRC funded project aimed at generating region-specific brain organoids and assembloids from multiple gene-edited human
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skills, with the ability to manage multiple tasks independently Commitment to equality, diversity and inclusion principles in research and team environments Desirable criteria Experience using wearable
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programme on children and young people attending the UK Gender Services because of gender incongruence. PATHWAYS is a research programme with multiple workstreams whose aim is to understand young people with
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(ideally in neuroscience) Ability to trouble shoot laboratory problems Ability to work collaboratively Ability to manage multiple tasks concurrently A commitment to creating an engaging and supportive
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English. Good time management and organisational skills, including ability to prioritise and manage multiple tasks. Desirable criteria Proven ability to work effectively within multidisciplinary research