72 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Tampere University" Postdoctoral research jobs at University of Oxford
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. The post is in association with a new Faraday Institution-funded project entitled “Accelerated Development of Next Generation Li-Rich 3D Cathode Materials (3D-CAT).” 3D-CAT is a new Faraday Institution
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with Professors Paul Harrison, Rachel Upthegrove, and Emma Mead. The postholder will receive strong mentorship and support for professional development, including training in new experimental and
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development opportunities such as mentoring graduate students, and developing project management skills. The project is based at the University of Oxford in the Department of Experimental Psychology, housed in
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relation to healthy urbanism. What We’re Looking For We’re looking for a Postdoctoral Researcher with: Demonstrable interest in urban health and/or sustainable urban development Relevant experience in
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collaborate with other technical groups working on the design. The successful candidate will also have opportunity to conduct experiments and machine development activities on the existing accelerators. The key
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samples and experimental models, with implications for autoimmune and metabolic disorders. As a Postdoctoral Researcher, you will primarily be responsible for the development, design, and execution
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to taking up the appointment. The research requires experience in the development of colloidal model systems, microscopy techniques and image analysis, and a detailed understanding of self and collective
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development towards optimizing and understanding sonochemical nitrogen fixation to help advance our internationally leading programme of research. This work will also contribute towards building a case for a
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models to understand the transmission dynamics of infectious diseases and generate insights to inform decision-making. The role will involve analysis of large epidemiological datasets, development
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geothermal processes along the volcanic arc, inform future field deployments, and serve as benchmarks for the development of new deep learning methods for volcanic seismicity. This project will apply deep