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continuum within the 2nd phase of CLICCS (https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System
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allowance. The employment will initially be limited to three years. Important: Applicants must not have resided in Germany for more than 12 months in the past three years. Group website: https://biophys.uni
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, and/or numerical mathematics, as well as an excellent command of a programming language, preferably Python or C/C++. The candidate should have an interest in modeling and solving a complex, coupled
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Python or C/C++. The candidate should have an interest in developing novel bivariate methods in machine learning for molecular property prediction within an interdisciplinary application. Ideally
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to interdisciplinary research approaches Publications in peer-reviewed journals demonstrating research expertise Proficiency in quantitative data analysis software (R, Python) and statistical methods Strong written and
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beneficial Experience in working with mouse models Advanced programming skills in Python are beneficial Strong motivation and ability to work both independently and collaboratively as a member of
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engineering, computational mechanics, modelling and simulation in CFD/FEA. Experience with scientific programming (at least Python and C++). Excellent written and spoken English. Very strong team working skills
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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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reliability, or fault-mitigation techniques. Strong programming skills (C/C++, Python; hardware-description languages “e.g., HLS, VHDL” is a plus). Motivation to pursue a PhD and contribute to applied AI
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, simulation, and software development (e.g., Python, C++, ROS, MATLAB) analytical skills and ability to combine theoretical modeling with experimental validation We are looking for first-class graduates with