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for the design of synthetic promoters and data analysis. PhD in (Plant) Biotechnology, Molecular Biology, Biochemistry or equivalent A publication record in peer-reviewed journals, and excellent proficiency in
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will include clinical and biomedical research projects. It will also involve methodological development aimed at combining imaging techniques and data analysis to provide a more integrated understanding
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-Gordon model, the scaling limit of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with
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. The project will also involve close collaboration with researchers from other disciplines within the Oxford Martin Circular Battery Economies Programme, who are working on second-life battery analysis, re
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skills, data management and analysis experience, problem solving skills, the ability and willingness to lead and organize a large research effort, and will work productively and enthusiastically with
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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radioisotopes to track sources and ages of different carbon components. The postdoc will lead the acquisition and analysis of aquatic water chemistry data, collected in different Arctic settings such as northern
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& coordination, drafting & revisions of protocols, amendments, & annual reports Data collection Data entry Data analysis and literature review Communications (e.g. develop knowledge mobilization strategy
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. Neuroimaging Analysis: Programming and prior experience with neuroimaging data analysis is required. Statistical Analysis: Solid foundation in statistical modeling and data analysis is required. Experience with
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-of-the-art IT infrastructure. Ideal candidates should hold a PhD in the area of Computer Science or Electrical and Computer Engineering and have strong programming skills including Python. Past work in