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well organized, structured, self-driven and enjoy interacting and collaborating with colleagues including PhD students, postdocs, and you are expected to take part in supervision of BSc and MSc students
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degraded DNA Analyse downstream population genomic metrics of extinct species Contribute to software documentation, tutorials, and user training Qualifications: A two-year master's degree (120 ECTS points
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strong background in industrial engineering, computer science, software engineering, energy systems, robotics, or related disciplines Interest in AI, simulation, and optimization for energy and industrial
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Analysis Software (e.g., OpenSees, Abaqus) is highly desirable. Ability to work independently and take initiative in planning and executing computational research. Willingness to join multi-national
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. Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable. Ability to work independently and take initiative in planning and executing
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, or predictive modeling—based on real experimental data. You will work closely with engineers, technicians, and the postdoc to build and refine data pipelines and interfaces. As part of your research training, you
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to engage in interdisciplinary collaboration and teaching. Good programming capabilities in advanced analysis software (e.g., Python, R, MATLAB, Julia, or similar) and mathematical optimization suites
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programming capabilities in advanced analysis software (e.g., Python, R, MATLAB, Julia, or similar) and mathematical optimization suites (e.g., GAMS, Pyomo, JuMP, or similar). Besides that, your ability and
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engineering and wave-wind theories is advantageous Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable Ability to work independently
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professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with the University of Leipzig (Bioinformatics, Prof. Peter Stadler