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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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The New York Times has called ?the most ambitious campus design program in the country." UC's momentum has never been stronger as the anchor of the Cincinnati Innovation District, the oldest cooperative
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in “Sustainable Metal Recovery—Hydrometallurgy & Circular Economy” within the framework of Doctoral Research School Program—BioGeoMetals, funded by the Swedish Research Council. Subject description
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28 Jan 2026 Job Information Organisation/Company Universität Siegen Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Application Deadline 11 Feb 2026 - 22
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Policy concentration for the MA program in a parallel role. This position works alongside the Associate Director of Initiative Operations and the Program Management team who are responsible for all
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16.02.2026 Application deadline : 15.03.2026 The Collaborative Research Center (CRC) 1233 “Robust Vision” brings together leading researchers in machine learning, computer vision, and systems
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Qualifications Experience: Relevant programming experience developing, implementing, debugging, and maintaining applications with Python. Experience working with high performance computers (e.g., parallelizing and
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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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the case of challenging environmental conditions, the method of multi-scale parallel single-pixel imaging has the potential to enable breakthrough advances. The “image processing and AI” group contributes
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research teams. Preferred Qualifications Experience with commercial and/or open-source GIS tools and technologies. Experience in parallel computing (e.g., MPI, Spark) and/or cloud computing (e.g., AWS