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Field
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of the position Simulate MRI data and model disturbances arising from various physical sources Develop, implement and train INR models for MRI time-series data Analyze functional MRI data of the spinal cord Present
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-10248 Requirements Skills/Qualifications Expertise in computer graphics and AI, possibly including physical simulation and PDEs. Knowledge of C/C
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tool for process design and laser-scanning strategies, the integration of simulation and experimental pulse-signal data to characterize lateral energy distribution, and the prediction of material removal
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Electric motors and the systems they drive consume half of global electricity. These systems are typically very inefficient and contribute to a significant amount of energy wasted. By physically
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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be given further consideration as candidates: Education Ph.D. in Electrical Engineering, Physics, Photonics, Optical Engineering, or a closely related field. As part of the RA Program you must have
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meetings. Documents required for the recruitment process CV copy of Master’s degree diploma (MA or MSc); application for the position of doctoral student; brief description of academic career to date; list
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3 Aug 2026 Job Information Organisation/Company Heidelberg University Department Institute for Theoretical Physics Research Field Physics » Computational physics Chemistry » Computational chemistry
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about shaping the future of AI
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principles” is essential for rational materials design, but the underlying numerical simulations are computationally expensive, limiting studies to small systems and short timescales. This project will explore