621 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected
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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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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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defence and security, working directly with industry and sometimes governmental or military collaborators. You are expected to have strong mathematical and programming skills, knowledge of computer vision
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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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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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analytical abilities, and a collaborative approach are essential. A clear vision for independent research and future funding is highly desirable. Those who have not obtained a PhD will be paid in the junior
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris