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computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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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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addition to salary, our Total Rewards benefits and Compensation Estimator give you a clear view of the complete package. Context of Job: As a Post-Doctoral Researcher, you will support Prof. Yuping Zeng with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
-lab.med.unc.edu/) has an open position for a computational postdoc to study the genetics of human disease. The successful candidate will analyze response QTLs (expression QTLs, splicing QTLs, chromatin
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may close at any time) Job Summary The Ho lab at the University of Utah is launching an ambitious program to systematically discover, map, and therapeutically harness mitochondrial microproteins
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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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learning algorithms for engineering systems Programming experience in FORTRAN, C, or C++ and scripting experience in Python or similar languages Experience with parallel computing environments and Linux
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate