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physics Physics » Thermodynamics Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Application Deadline 19 Apr 2026 - 23:59 (Europe/Brussels
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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State University of New York University at Albany | Albany, New York | United States | about 13 hours ago
vibration isolation). In parallel to the benefits of quantum computing, artificial intelligence and neuromorphic computing seek to emulate the massively parallel, highly efficient computing capacity
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legal practitioners and risk managers to pursue research questions with practical applications. SSLA's Social Science Research Professional position is designed for recent college or master's program
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position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Computer Science This Ph.D. project will develop fundamental theory and methods in distributed systems
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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, for example: Large‑scale optimization and machine learning: Stochastic and/or (non‑)convex optimization methods, first‑order methods, variance reduction, distributed and parallel optimization, federated
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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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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
(supercomputer/cloud/edge) infrastructures. Developed by the KerData research team in the context of the STEEL project of the national PEPR CLOUD program, E2Clab (https://team.inria.fr/kerdata/e2clab/ ) is a
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including workload schedulers, storage systems, and distributed compute nodes. Applies analytical methods to evaluate system performance, identify bottlenecks, and implement corrective actions to improve