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start: Structured induction • Healthy at work: Numerous health promotion offers, free membership in UKBfit • Employer benefits: preferential offers for employees (corporate benefits) The University
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
(VBL) # We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours # Numerous company health management offerings # Employee discounts
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solutions and dual career options We provide support with various qualification and further training opportunities and use of the Haufe learning platform with numerous different online courses Application
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platform with numerous different online courses Please apply online through the FLI application portal by 30.04.2025. https://jobs.leibniz-fli.de/836wn FLI is proud to be an equal opportunity employer and
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department collaborates with numerous national and international partners and with local clinical and research departments. We offer a dynamic, interdisciplinary environment with extensive training
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc.. You will be involved in all phases of this process. You will
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Proficiency in running numerical coastal ocean models Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting Strong programming skills, preferably in Fortran, C/C++, or Python
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ecosystem models. Experience using high-performance computing systems. Proficiency in running numerical ocean models. Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting
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reporting skills (4) Experience in spatial data analysis using geographic information systems (GIS) and programming languages (R, Python) as well as experience in numerical model applications and multivariate
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to the Baltic Sea region. Experience in running numerical ocean models and analyzing ecosystem model output. Experience using high-performance computing systems. Familiarity with operating systems such as Linux