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flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO) Proficiency in scientific programming using Python, with
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit
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Python and R; - Demonstrable experience with Machine Learning; - Excellent problem-solving skills and the ability to work both independently and as part of a team. This position is for full-time, on-site
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Python and common deep learning frameworks (PyTorch) • Excellent communication skills in English (German is a plus) • Independent, structured working style and experience in supervising students Preferred
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, MetaPhlAn, or similar). Proficiency in programming languages for data analysis (e.g., R, Python). Experience with mass spectrometry-based metabolomics approaches, including LC-MS/MS. Experience operating
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, including languages such as Java, C/C++, C#, Python and JavaScript, as well as web technologies including HTML, CSS and AJAX/JSON-based APIs. Experience with database systems, including relational and non
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training in nuclear physics and/or nuclear reactor physics. Strong programming skills (Python and/or C++) and data analysis skills are required. Proficiency in stochastic neutron transport simulation
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reactor physics. Strong programming skills (Python and/or C++) and data analysis skills are required. Proficiency in stochastic neutron transport simulation software such as MCNP, Serpent 2, OpenMC, Tripoli
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optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience using scientific computing and optimization libraries
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning