2,033 parallel-and-distributed-computing-"UNIS" Postdoctoral positions in United States
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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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Electrical Engineering, Computer Science, Operations Research, or a closely related field. Experience in power systems, distribution systems, or microgrid modeling, with a solid understanding of advanced co
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variety of conditions, in particular seeking evidence for Fermi acceleration of electrons under low-to-moderate guide magnetic field and parallel electric field energization under large guide magnetic field
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Position Summary The GrandPre group in the Department of Physics at WashU in St. Louis invites applications for a theoretical/computational postdoctoral position, with an anticipated start date
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Science. The position will begin in August 2025. The position includes teaching courses in the Applied Behavior Analysis and Clinical Science master's program. The teaching load is 24 credit hours to be
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with ab initio methods. Proficiency in software such as VASP, Quantum ESPRESSO, Critic2 and Gibbs2. Experience in high-performance computing and parallel processing. Additional Qualifications Considered
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-learning trained using the van der Waals corrected hybrid density functional theory (DFT) enabled SeA approach [J. Chem. Theory Comput. 19, 4182 (2023)]. The SeA approach is an accurate and efficient high
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closure modeling and/or high performance computing environments (MPI, CUDA) • Expertise in software development and computing tools (C/C++, python, git, parallel computing, etc.) • Experience with deep