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Field
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Computer Science or related fields Experience in power system modeling, optimization, and control Experience in at least one of the power system software tools including OpenDSS, PSCAD, PSS/E Experience in at least
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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. Strong experience developing, deploying, and optimizing applications and workflows in high-performance computing (HPC) environments. Demonstrated programming proficiency in C/C++ (preferred) and Python
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foundations, focusing on the structure and complexity of quantum computational models; (ii) optimization and related graph-theoretic methods, using polyhedral geometry and algorithmic optimization (e.g., vertex
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languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in optimization, image-guided radiotherapy, medical imaging, or computational modeling. Experience with treatment
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particle trapping and related measurement techniques. Relevant skills include understanding of fundamental principles, design, optimization, computational electromagnetic, mechanical and thermal modeling
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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motivated Postdoctoral Researcher to join our Grid Planning and Analysis Center (GPAC). This position will focus on tackling critical optimization challenges in medium-term power system planning like
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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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experimental animals Experience implementing and optimizing eye tracking, body tracking, and/or visual reality environments Proficiency in Python and scientific computing libraries Familiarity with spike sorting