77 programming-"DAAD" Postdoctoral positions at University of Oxford in United Kingdom
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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ability to contribute ideas for new research projects and research income generation. Previous research experience in one or more areas relevant to the research programme. For example: probabilistic machine
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specialist knowledge in mechatronics design and control, and proven programming experience in Python, MATLAB or C/C++. Informal enquiries may be addressed to Professor Liang He (email: liang.he@eng.ox.ac.uk
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anxiety, to work within the established research programme. Substantial hands-on research and professional experience of working with individuals with mental health difficulties, including first-hand
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is