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attitude. We consider it a plus if you bring the following: experience with microscopy and molecular biology techniques; programming skills (e.g. good command of R, basic command of Linux); affinity with
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; additional experience in one or more of the following areas is highly desirable: stochastic simulations quantitative genetics breeding programs working with Linux and HPC systems For this position your command
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is highly desirable: big data analytics quantitative genetics variance component estimation working with Linux and HPC systems For this position your command of the English language is expected to be
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element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux operating systems Structured and analytical
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learning models, and willingness to learn about new methods, is a plus. · Strong programming skills in Python, and Linux Shell; experience in developing methods as open source repositories at e.g. GitHub is
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workflows. Familiarity with Linux/HPC environments (for the modeling position). Experience with data visualization or handling large datasets. Demonstrated interest in climate physics and/or cross
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MONAI framework. Working in a Linux environment, with experience of shell scripting, cluster, or cloud computing. Fluency in spoken and written German. We are looking forward to receiving your
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-on experience with Federated Learning frameworks. Hands-on experience with MONAI framework. Working in a Linux environment, with experience of shell scripting, cluster, or cloud computing. Fluency in spoken and