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Field
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(beyond model training) Solid programming skills (Python required; C++/CUDA a plus depending on simulations) Interest in physics-based simulation, numerical methods, or computational engineering Motivation
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, geoinformatics, geoecology or related fields Programming skills (Julia, Python, MATLAB) and ability to work with time series and/or geospatial data Motivation to work at the interface of ML and environmental
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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languages (e.g. Python) Very good command of English (oral and written) Additonal skills and experiences that are advantagous: Experience in ocean dynamics Experience in ocean and/or biogeochemical modelling
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, ecology, mathematics, or a related field Strong programming skills, preferably in Python (experience with scientific computing, ML frameworks, high performance computing and geospatial data are highly
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to apply E-mail personal@ufz.de Website https://recruitingapp-5128.de.umantis.com/Vacancies/3391/Description/2 Requirements Additional Information Website for additional job details https://recruitingapp
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Experience in quantitative data analysis and in handling complex bodies of data in the use of at least one programming language (e. g. Python, Java ...) Language skills (CEFR-Level): English at least C1
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. Experience in programming (in particular, Python) and an interest in machine learning, data analysis, or scientific computing are expected. Prior experience with machine learning or optimization methods is
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, e.g., Python, C/C++, Fortran Willingness to work independently and think critically Excellent communication skills Ability to work well in a team and contribute to a diverse and inclusive workforce What
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics