61 computer-science-programming-languages-"St"-"St" Postdoctoral positions at Argonne
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The Environmental Science Division at Argonne National Laboratory is seeking a postdoctoral researcher to join a project aimed at improving model representations of carbon cycling and greenhouse gas
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vigorous research programs. Position Requirements A PhD in physics, materials science or related field; Must have been received within the last 5 years or upcoming year Significant written and oral communication
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your PhD in computer science or engineering, the physical sciences, or a related field within the last five years. Comprehensive programming proficiency, preferably in Python. Experience with machine
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optimization, with experience in adaptive routing and SDN technologies. Proficiency in programming languages such as Python, C/C++, and experience with parallel computing frameworks. Effective written and oral communication
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engineering, or a related field. Demonstrated expertise in process modeling, process optimization, and technoeconomic analysis. Programming skills in scientific computing languages such as Python and Julia
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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) or equivalent experience in a computational science discipline, computer science, or in a related field Strong programming skills in one or more scientific programming language, such as C++ and Python Experience
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and oral communication skills Requirements: Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field Ability to
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and contract. Skill in modeling, processing, and analyzing computational results to inform accompanying experimental efforts. Skill in the use of modern collaborative coding practices. Demonstrated
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, project presentations, and other regular channels. Position Requirements Skill in modeling, processing, and analyzing computational results to inform accompanying experimental efforts. Skill in the use