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supercomputing facilities. Knowledge of numerical methods for large-scale simulations of fluid flow, heat transfer, and chemically reacting systems. Documented ability to work effectively in interdisciplinary
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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people who discover them The Opportunity Join an ARC-funded research project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims
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network architectures for AI compute clusters utilising optical switching and numerically assess the performance via software simulation tools. Define the system specifications which will be then translated
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
presents multiple theoretical and practical challenges. Supercomputers currently have the capacity to support the large-scale executions of numerous numerical simulations. This makes it possible to carry out
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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an interdisciplinary team that works on cutting-edge questions ranging from mathematics and theoretical physics all the way to numerical simulation algorithms? Then apply now to join our team of researchers in
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7th October 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in High Performance Computing and Simulation Apply for this job See
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discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we
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numerical simulation of photonic neural networks (PNN) using Python, Photontorch, and/or SAX Assistance in the creation and verification of PIC layouts and specifications for the photonic neural processor