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focus on the development of new theoretical frameworks, implementation of new methods in first principles computational modelling packages, and direct application to representative solid state systems
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areas include: • Investigate innovative financing models for circular bioeconomy businesses and value chains, such as food, fashion, and health. • Explore non-market mechanisms
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As part of the Oxford Martin School Digital Pandemic Preparedness Programme and the Leverhulme Centre for Demographic Science (LCDS), Nuffield Department of Population Health (NDPH) are recruiting a
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to join the Oxford-Novartis Collaboration in AI Medicine team at Nuffield
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at the University of Oxford. The position is funded by the EPSRC-FNR project “FleXEdge - Data-Driven Cloud-to-Edge Computing for Scalable Near Real-Time Local Flexibility Markets”. It is fixed-term for 36 months
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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are seeking a
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science, engineering) and possess experience of developing statistical and computational models using AI. For an informal discussion about the post, please contact Dr Christopher Yau (christopher.yau@wrh.ox.ac.uk
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Computational Methods for Advanced Research to Transform Biomedicine ( SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and
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, computational sciences, physical sciences, or mathematics, together with sufficient specialist knowledge and hands-on experience in the CFD simulation of internal combustion engines, and in particular in-cylinder
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genetic causes of neurological disorders and aim to develop therapies for such conditions with a high complementary approach, ranging from stem cell modelling to functional genomic. Enhancers play a pivotal