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Field
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), including the use of HPC clusters Programming skills in data processing and hardware control (e.g. Python, Labview, Matlab, C++) Project management experience: setting goals, prioritising tasks, and meeting
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, genetic variation, and viral evolution. Genomics & Bioinformatics: Viral genome-based evolutionary analysis, Linux/HPC-based analysis, and NGS workflow development (e.g., Snakemake, Bash). Key
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, Linux/HPC-based analysis, and NGS workflow development (e.g., Snakemake, Bash). Key Responsibilities The appointee will join a vibrant multidisciplinary team focusing on emerging infectious diseases. He
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and a desire to work in a team-oriented, interdisciplinary environment This position offers access to state-of-the-art facilities (e.g., High Throughput Bioscience Center, link, and HPC environment with
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trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
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with national/international collaborators from the ODUST consortium. • Access to HPC resources (e.g., IDRIS) for large-scale simulations. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR5299
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the McGill BioPortal. Develop and maintain reproducible analysis pipelines in R, Python, and shell on HPC / Slurm clusters and cloud environments (e.g., DNAnexus, Terra, AWS/GCP). Write first-author
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pragmatic, iterative mindset - prioritising what works empirically and is testable over purely theoretical correctness. Valued: Experience with high performance computing (HPC). Prior exposure to mass
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studies of organic, organometallic, photoredox, radical, or homogeneous catalytic systems. Fluency with Python and modern scientific computing workflows; experience with Git, HPC clusters, SLURM, Gaussian
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data