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to optimize performances. The postdoc will carry out structural and morphological characterizations (X-ray diffraction, TOF-SIMS, AFM, and microscopy) of the selected superconducting materials. In the second
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Physics, Applied Mathematics, or Computer Science, with experience in deep generative models (VAE, diffusion) and Python/PyTorch. Applications from statistical physicists are welcome. STILL HESITATING? The
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further supports efficient design space exploration via optimization strategies. This role is part of EU-funded research projects on next-gen HPC networks and open-source EDA tools, with a focus on optical
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Numerical analysis of fully explicit phase-field models for dynamic fracture of materials H/F Numerical analysis of fully explicit phase-field models for dynamic fracture of materials Understanding material fracture is paramount in the nuclear industry to ensure the structural integrity and...
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of market-making algorithms (for threshold selection, and finding the optimal size of windows/batches)