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We are seeking a full-time Postdoctoral Research Assistant in Computer Vision to join the Visual Geometry Group (Central Oxford). The post is funded by ERC and is fixed-term for 1.5 years with a
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project and is fixed-term for two years, with the possibility of extension. The objective of this project is to carry out computer vision and machine learning research in order to be able to translate
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sustainable alternative to conventional rubbers, thanks to their re-processability, recyclability, and design flexibility. A micromechanical approach will be adopted to link key microstructure parameters (hard
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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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regulation, water purification, provisioning fisheries for the implementation of EU and global policies . Complimentary measurements of dissolved CO2 , CH4 and other water quality parameters via sensors and
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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scientific discipline. Experience in developing and running an atmospheric transport model. Experience in interpreting data. Experience with FORTRAN and Python computer languages. Proven ability to 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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of computer simulation models that are open for reuse by health researchers and the NHS. The post holder will conduct cutting edge research that builds on our preliminary research with Open Weight Local Large
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methodological and biological factors—such as the choice of substitution models, site saturation, and the role of selection, mutation, and recombination—that shape evolutionary rate estimates. A key goal is to