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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Diseño y desarrollo de extensor
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including knowledge of PyTorch, Tensorflow, Pandas, Scikit-learn and/or Numpy. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques. Fluency in spoken and written
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. Additional Knowledge and Professional Experience Experience with high-performance computing (HPC) environments and parallel programming (e.g., MPI, OpenMP). Experience with the management and analysis of large
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materials technologies. We focus on the unique physical properties and disruptive application potential of two-dimensional materials, leverage intelligent materials design and multi-scale computational
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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-Based Generative Models: How can we fundamentally redesign generation processes for superior efficiency, controllability, and quality? We are exploring diffusion models, flow-matching, and other parallel