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Field
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ML to interpret or guide experimental work. High-performance computing (HPC) and data management for large-scale materials datasets. KEY SELECTION CRITERIA Join us if you have: Doctorate degree from a
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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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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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biology approaches and early-adoption of cutting-edge technologies Operating with Linux and high-performance clusters (HPC) R/Python and Snakemake or Nextflow (or comparable platforms) OUR REFERENCES
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suitable evolutionary models Development and implementation of novel phylogenetic approaches, including those implementing protein structural information. Where to apply Website https
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of this document online: https://sdrive.cnrs.fr/s/Lcp3L3Xb2ZQ2xpm Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7371-DMITOD-002/Candidater.aspx Requirements Research FieldNeurosciencesEducation
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-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery
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are looking for highly talented developers with experience and interest in state-of-the-art technologies, high performance computing (HPC), memory management, and dev-ops. You will enjoy being part of a world
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resources, including group-owned HPC clusters with PB-scale storage. Opportunities for professional development and international collaboration. How to Apply The University only accepts online application
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) Where to apply Website https://recrutement.univ-lr.fr/filo2/login Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications We are seeking a highly-motivated