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-informed ML Experience working with Linux and HPC environments is an advantage. Strong communication skills and excellent proficiency in English. You enjoy working in an international, interdisciplinary team
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, Quantitative Genetics, Population or Statistical Genetics). Demonstrated experience in analytical and quantitative skills. Proficiency in programming and data analysis tools (e.g. Python, R, Fortran, Linux
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functional groups. You will implement parameterisations for the effects of wind farms in GETM-ERSEM-BFM, run relevant scenarios to investigate the effects on the NIOZ high performance Linux cluster, and
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-grained models Experience with advanced simulation and analysis methods (e.g., LAMMPS, HOOMDblue, advanced analysis workflows) Strong programming skills (e.g., Linux, C++/Fortran, scripting languages