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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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performance, detect artefacts, and ensure scientific rigor Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis Ready to work with time‑series data, sensor fusion
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measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Practical laboratory skills and an enthusiasm for experimental work are highly
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effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Participation in teaching
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sustainable future. A more detailed summary of our research fields can be found on: https://www.isse.tu-clausthal.de/forschung/forschungsgruppen/dgt-digitized-green-tech Our excellent network on international
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fields can be found on: https://www.isse.tu-clausthal.de/forschung/forschungsgruppen/dgt-digitized-green-tech Our excellent Network on international and national basis offers a perfect start for a
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analytical programming language (e.g., Python, R) or a universal programming language (e.g., C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills
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quantitative medical imaging Proficient programming skills in at least one object-oriented language (e.g., C++, Python) and broad understanding of common programming paradigms, including object-oriented design
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for mathematics Experience with programming (e.g. Python, C++, CUDA etc.) Knowledge of information theory Good reasons to join: Look forward to a unique working environment on our international research campus