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Description of the offer : To further advance and refine novel techniques—such as x ray detected ferromagnetic resonance (XFMR) with polarized soft x rays in reflectivity and diffraction geometries—to investigate magnetization dynamics. The goal is to precisely resolve the static and layer...
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this date, in both directions). The position is funded by NERC grant 'High Resolution Radar Imaging of Pyroclastic Density Currents', in collaboration with University College London, and the University
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Postdoctoral Research Associate in Radar Imaging of Geophysical Flows ( Job Number: 25000801) Department of Earth Sciences Grade 7: - £38,249 - £45,413 per annum Fixed Term - Annualised Hours (Full
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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50 Faculty of Life Sciences Startdate: 01.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.07.2031 Reference no.: 4188 At the University
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validate mechanical and electronic systems for image-guided therapy. Integrate pioneering and proven tools for the precise control and validation of interventional device placements. Examine clinical
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experimentally validate mechanical and electronic systems for image-guided therapy 2) Integrate pioneering and proven tools for the precise control and validation of interventional device placements 3) Examine
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image