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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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redox balance. Our studies explore how p53 integrates metabolic cues by acting as both a sensor and regulator of cellular metabolism. In parallel, we are identifying metabolic changes that promote tumor
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detection efforts. In parallel, any ocean word biological productivity will almost certainly fall orders of magnitude below that on Earth, leading to lower concentrations of target compounds and/or longer
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capabilities, and particularly the Experimental Medicine Clinical Research Facility (EMCRF) (https://www.kennedy.ox.ac.uk/news/oxford-and-gsk-launch-experimental-medicine-collaboration). This will allow testing
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to enable massively parallel processing of ABMs on NVIDIA graphics processing units (GPUs), without the need for specialist understanding of GPU programming or optimisation. This project will explore
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setup will allow the exploration of global flow structures, large-scale recirculation, and the transition to the fully heterogeneous regime under realistic industrial conditions. In parallel, smaller
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several projects in parallel Ability to work collaboratively in a team as well as independently on a wide variety of research projects Excellent communication skills Detail-oriented, focused, and highly
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of the developed process will be explored through parallel screening and the selectivity of the catalysts refined through subsequent rounds of catalyst design. The successful candidate will work within the
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both