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potentials or force fields (for example MACE, NequIP, DeePMD). ● Experience running scientific calculations on Linux-based high-performance computing clusters, including scripting or workflow automation
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computing tools in a Linux or Windows environment. Experience with scientific data visualization and preparation of figures for presentations or publications. Graphic design experience and the ability
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, environmental engineering, or a related field. Experience in numerical hydrologic models and land surface models. Experience with Linux on cluster and/or high-performance computing environments. Experience
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, biostatistics, computational genomics, longitudinal data analysis, or a related quantitative field; proficiency in R and/or Python and experience working in Unix/Linux computing environments; experience managing
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programming skills in R. Proficiency working within UNIX/Linux environments. Preferred Qualifications Experience with Bayesian statistical methods. Experience with hierarchical modeling and mixed effects models
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). Candidates must have excellent quantitative, writing and communication skills. Expertise in R, Matlab programming, Linux computing, and familiarity with neuroimaging software tools (FSL, AFNI, SPM) is
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data assimilation systems on Unix/Linux and high-performance computing platforms. Evaluate model and assimilation performance using statistical and dynamical diagnostics and verification against
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biological or genomic datasets. Proficiency in programming languages commonly used in scientific computing (e.g., R, Python, Linux/Unix environment). Excellent analytical, written, and verbal communication
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Python and experience working in Linux and high-performance-computing environments. Experience developing or using automated and reproducible computational research workflows. Ability to conduct
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language. Working knowledge of UNIX or Linux. Preferred Knowledge, Skills, and Experience Experience with machine learning and accelerator operation. Experience working with complex algorithms. Experience