97 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at University of Oxford
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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces
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We are seeking a Postdoctoral Research Associate to support our projects to understand membrane evolution. The aim of this project is to use molecular dynamic simulations to understand membrane
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concept of agents has come to the fore again, prompted by the rise of Large Language Models (LLMs) – put crudely, the idea is to use LLMs, in the sense of being powerful general purpose intelligent systems
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- Develop original numerical methods for facility simulation in presence of expansion waves - Demonstrate improved estimates of rate constants for two-temperature models - Contribute
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& NCO & CDO, etc.), and have demonstrable expertise in the analysis of big data, and the interpretation of climate/weather observations/reanalyses and model simulations. Additionally, experience with
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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incorporated into cellular function. We are now looking for a postdoc to study the physicochemical properties of membraneless organelles and the links to neurodegenerative disease. The candidate will have
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on single-agent settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems