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Field
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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analysis of large data sets Prior experience in signal transduction research Knowledge, Skills and Abilities: PhD level knowledge and understanding of basic cellular and molecular biology Expertise in cell
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development. Basic Qualifications: A PhD in computer science/engineering, electrical engineering, data science or a related field completed within the last five years. Experience of AI and efficient computing
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multivariate data analysis. Preferred Qualifications: PhD in Chemistry, Materials Science or Chemical Engineering. Candidates are expected to have a strong background in quantitative structure analysis based
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high fidelity models of ice crystal icing accretion and shedding, verifying tools using the wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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O’Brien’s research groups at the Department of Engineering Science (Central Oxford). The post is fixed term for two years and is funded by the EPSRC. The development of large-scale quantum computers will
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of enabling large-scale redox flow battery deployment for energy storage. Scope of Work The successful candidate will work on: Designing and optimizing extraction processes for vanadium from primary and
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future funding. Required Education and Experience Appropriate PhD in a related field Preferred Qualifications Willingness to work with large animal models Experience with tissue culture and primary cell
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Vacancies Postdoc position on Data enhanced physical reduced order Models Key takeaways The position is embedded into a large-scale effort between academic groups in the Netherlands and industrial
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science