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, numerical optimization, numerical partial differential equations, and parallel computing. The Researcher will join a project developing parallel high-order meshing algorithms from medical images and parallel
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. This project employs massive-scale genome sequencing, data that will enable a wide range of novel, independent projects. The project also involves a substantial theoretical component including algorithm
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researchers will develop computational workflows and incorporate resilience assessment algorithms into a decision support platform using Jupyter notebooks. The work will include development and use of virtual
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techniques relevant to neutrino oscillation experiments. Experience and ability in particle physics data analysis. Experience and ability with algorithm development and C++/Python programming languages. Good
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, upgrades/development and/or operation. Experience in the development and/or training of machine learning algorithms. Good communication skills. Contact Information to Applicants Professor Elliot Reynolds