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cancer genomics and functional interpretation of genetic variants Proficiency in Python, R, or other bioinformatics languages Knowledge of cloud computing, and high-performance computing (HPC) environments
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. Apply and upscale models to industry-relevant scenarios, deploying simulations on high-performance computing (HPC) infrastructure and integrating outcomes into commercial workflows. Collaborate and
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modelling, including two-phase flow in fractures, stochastic permeability analysis, and upscaling to fracture networks. Deploy large scale simulations using high-performance computing (HPC) and collaborate
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data Ability to mentor and develop bioinformaticians at all stages of the analysis project workflow Desirable criteria Excellent computational skills applied to HPC, big data, software development and
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: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
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bioinformaticians at all stages of the analysis project workflow Desirable criteria Excellent computational skills applied to HPC, big data, software development and web technologies Experience in teaching
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bioinformaticians at all stages of the analysis project workflow Desirable criteria Excellent computational skills applied to HPC, big data, software development and web technologies Experience in teaching
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to develop data-driven, space-time explicit precision agronomic solutions Utilizing high-performance computing (HPC) systems for large-scale geospatial data processing, model training, and validation Designing
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been oriented around high performance computing (HPC) but are increasingly migrating to cloud-based solutions. We are seeking a talented software engineer to bring in this transition. You'll Be Solving
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tools for High-Performance Computing (HPC) applications. Qualifications/Requirements Qualifications / Discipline: - PhD’s degree in Physics, Materials Science, Computer Science, Data Science, Artificial