230 computational-physics-"https:"-"https:"-"https:"-"https:"-"Dr" Postdoctoral positions in United Kingdom
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working in a University that has made significant contributions to society, medicine, physics and teaching for over four centuries. Our people have helped create the modern world and are working on more
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, meaning that familiarity with one or more cloud-based platforms such as Google Earth Engine, Microsoft Planetary Computer and/or Amazon Web Server/similar is essential. It will also involve the development
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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis
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to reduce inequality in high-income countries, and/or (3) the study of social mobility and its relationship to economic inequality. The post holder will work with the INET Oxford programme on Economics
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computing in a Linux environment A record of presenting your research at scientific conferences Excellent knowledge of written and spoken English (C1) A commitment to collaboration and communication within a
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towns programme, organise and run patient and public involvement events to engage with community members and innovate, contribute to and promote the research, publication and impact focus of the centre in
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such as computational social science, computer science, or cognitive science. They will have a demonstrable track record in studying humans and machine learning models, in the context of human social
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will contribute to an exciting, interdisciplinary programme developing next-generation human in vitro models of pain. The project aims to recreate the complex multicellular interactions that underlie
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to the ‘Biological Nitrogen Fixation’ program. This initiative seeks to engineer biological nitrogen fixation into widely grown crop plants to improve yields and reduce global reliance on synthetic fertilisers
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Planetary Physics (AOPP) sub-department of the department of Physics, at the University of Oxford. The post will address a significant problem in climate forecasting known as the Signal-to-Noise Paradox (SNP