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We seek to appoint a Research Associate (postdoctoral scientist) to join the prolific climate/weather/environmental and impact science community at the University of Oxford, that is interested in playing a crucial part in the outcomes and deliverables of the multi-institutional NERC-funded...
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including conditional diffusion and flow matching models for synthesising Magnetic Resonance Imaging (MRI) and predictive analysis for Novartis Oxford collaboration for AI in medicine. The collaboration
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. This project will require a strong molecular biology background, knowledge in AI-based protein structural prediction, in vitro expression systems and cryo-EM, experience in analyzing large datasets, and solid
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interactions. We’re Looking for Someone With: Strong expertise in protein structure prediction, molecular modelling, and docking. Proficiency in LINUX, bash scripting, and high-performance computing environments
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innovation in global health. You will work as part of the SchistoTrack team, a prospective cohort study that investigates predictive factors for schistosomiasis-associated morbidities across rural Ugandan
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Atmospheric Dynamics group in AOPP which looks at the role of dynamical processes globally in weather and climate variability, predictability and change. The role will involve detailed analysis and dynamical
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advanced fundamental physical understanding of the phenomena at play but accurate predictions in realistic geometries remain difficult. You will be responsible for implementing and validating ice accretion
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between environmental stressor (e.g. temperature and dissolved O2) better predict extinction risk than any variable alone. About you You will hold or be close to completion of PhD/DPhil together
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including protein purification, SDS-PAGE, and western blotting. The post holder should be familiar with bioinformatics tools and databases (BLAST, protein structure prediction tools) and have basic
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structural), ECG, and genetics, to model disease trajectories and improve risk prediction in cardiomyopathies. The successful applicant will work closely with the PI to deliver research projects, supervise