149 computational-physics-superconductor Postdoctoral positions at University of Oxford in United Kingdom
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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part of a wider programme of work to establish that membraneless organelles, biological liquid droplets, are effectively regions of organic solvent, suspended inside cells and that the properties of each
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of a wider programme of work to establish that membraneless organelles, biological liquid droplets, are effectively regions of organic solvent, suspended inside cells and that the properties of each
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The Oxford Internet Institute has an exciting opportunity to join the Governance of Emerging Technologies research programme, working under the supervision of Professor Brent Mittelstadt and
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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measuring a molecule’s size and shape in the solution phase (Science 2025). Our microchip-based escape-time technology platform now enables measurements of the physical properties of macromolecules such as
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support a high-value materials characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas
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on process development, electrode manufacture and performance assessment, but depending on the skills of the successful applicant, may also involve some aspects of modelling or data science. The post is funded
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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experimental and computational approaches are employed to shine light into key biological processes during the life of parasitic flatworms. Large-scale sequencing datasets (‘omics’) are generated and analyzed