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Field
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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: - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics. - Experience with High-Performance Computing (HPC) systems and intelligent
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-Performance Computing (HPC). The postdoctoral researcher will have opportunities to engage in these areas in support of physics goals. Key responsibilities Lead and contribute to ATLAS physics analyses Develop
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oriented to improve digital skills. Access to CSIC infrastructure (e.g., HPC, Bioinformatic and Computational Biology Connection) Where to apply Website https://docs.google.com/forms/d/e/1FAIpQLSeGVtNv_
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, classification, and interpolation of pixel detector data. Exploration of spike-based data encoding/decoding strategies. Hyperparameter optimization using advanced computing resources (e.g., HPC clusters). Detector
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large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS. The position requires a PhD in a relevant field, strong bioinformatics and
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Supercomputing Centre (BSC-CNS), and in coordination with the developers of the other MaX flagship codes, a shell of leading European HPC centres, and selected European private-sector technological partners
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with the ability to meet deadlines and produce publishable research. Experience with deep learning applications in seismology, using high performance computing (HPC) environments, field experience with
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exceed 15% of gross income. Access to state-of-the-art facilities and resources, including group-owned HPC clusters with PB-scale storage. Opportunities for professional development and international
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unique opportunity to work at the forefront of therapeutic genomics, leveraging large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS