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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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, and Munich. The role: The position aims to develop predictive computational models of epigenetic dynamics, in close collaboration with Prof Rob Klose’s experimental group (Biochemistry, Oxford
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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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set to deliver an ambitious research vision and where you can contribute to the training of PhD and Master’s students. You are excited about opportunities to communicate with international collaborators
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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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patients with hearing disorders. You will join a collaborative environment where your technical expertise in computer vision will contribute to clinical applications. Our team are now expanding our work
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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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(model performance) and quality studies (human factors assessment). You should hold a relevant PhD/DPhil (or be near completion) in computer vision or robotics or biomedical image analysis. Knowledge
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Laboratory in the ‘Digital Innovation Facility’ at the University of Liverpool. You will possess, or be close to completing, a PhD in Electrical Engineering / Electronics / Computer Science or a relevant