181 parallel-computing-numerical-methods research jobs at University of Oxford in United Kingdom
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences and skills of the successful
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atmospheric physics, meteorology, climate, numerical methods, and data science. The Research Associate will be proficient in programming/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script
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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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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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is necessary for consolidation of learning, and we therefore seek to explore how sleep changes over time with recovery, how this relates to learning and consolidation, and test novel methods
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of computational biology, molecular biophysics, and cutting-edge analytical technologies. You’ll contribute to the development and application of computational methods to understand protein folding, structure, and
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for supporting the effective governance of AI. You will lead the Technical AI Governance programme and develop research questions within AI safety, interpretability, and technical governance. You will also
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effects. You will contribute to the numerical modelling part of the project, which will benefit from novel element level and centrifuge testing experimental results. You will set up and validate numerical
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to enable robust robot autonomy in complex, real-world environments. The post sits within our EPSRC Programme Grant in Embodied Intelligence and will advance the state of the art in localisation and scene