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Field
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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operation · Application of artificial intelligence or machine learning in energy or engineering systems 5. Strong programming and modelling skills using relevant tools such as Python, MATLAB
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to work on meaningful projects with direct clinical relevance. About the role In this role, you will develop and implement computer vision and deep learning algorithms to analyse CT and MRI data from
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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reinforcement learning and machine vision. Experience with ROS and the ROS ecosystem Special Requirements: Applicants cannot have received their PhD more than five years prior to the date of application and must
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image