9 parallel-computing-numerical-methods Postdoctoral positions at University of Texas at Arlington
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. Experience in developing and applying advanced parametric/machine learning postprocessing techniques, producing probabilistic forecasts of hydrometeorological variables, and parallel computing. Proficiency in
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, Climate Science or a related field. Experience in earth system modeling, data assimilation, and remote sensing of land surface variables. Experience with parallel computing on high performance cluster
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-of-the-art computational and statistical methods for integrative analysis of multi-omics datasets. Utilize high-performance computing environments to process large-scale datasets and analyze large-scale
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of Engineering at the University of Texas at Arlington invites applications for a rank Post Doctoral Research Associate. This position will focus on analyzing imaging data, developing novel methods for analysis
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and integrating computational modeling tools to assess future energy-water dynamics and resilience strategies for Texas communities. Ideal candidates should have strong computational and scientific
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an area related to COSMOS, including degrees in operations research, industrial engineering, statistics, computer science, and mathematics. Preferred Qualifications Completed dissertation research related
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an area related to COSMOS, including degrees in operations research, industrial engineering, statistics, computer science, and mathematics. Preferred Qualifications Completed dissertation research related
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comprehensive engineering program in North Texas, with 12 baccalaureate, 13 Master’s and nine doctoral programs. The University is classified as a Research 1 University — Highest Research Activity by the Carnegie
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proven track record in reservoir modeling, optimization, and high-performance computing. Proficiency in C/C++ and Fortran. Good verbal and written communication skills. Preferred Qualifications Experience