129 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at University of Oxford in United Kingdom
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scientists, forming small teams focused on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor
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lab has developed the OrthoFinder comparative genomic methods. OrthoFinder has become widely-used in comparative genomics research, it powers many popular databases of online genomic information, and
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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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administrative duties and provide guidance in machine learning methods to less experienced members of the research group, participate in the dissemination of research outputs, and carry out collaborative projects
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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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understanding of dark energy. Projects may span a broad range of topics, including improving Type Ia supernova modelling and standardization, developing and applying advanced data analysis and statistical methods
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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
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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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