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river delta models. Demonstrable ability to use programming languages such as Python, Julia, C, C++ or Fortran. Familiarity analysing functional diversity and/or geomorphological information. Curiosity
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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-performance computing systems Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting Strong programming skills, preferably in Fortran and Python Competency in visualizing and
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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development knowledge of the state-of-the-art in climate physics and Earth system modeling and data analysis techniques programming skills e.g. in C, BASH, Python, Latex software user knowledge: MS or Libre
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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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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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and