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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
., using FEniCSx) Advanced knowledge of scientific programming, preferably in Python, including experience with implementing machine‑learning methods (e.g., PyTorch) Excellent spoken and written English, as
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: MATLAB, Python, LaTeX. • You have excellent command of written and spoken English. What we offer: Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair
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quantum foundations. • You have experience in academic writing. • You should have experience with the usual tools for advanced experiments: programming experience: MATLAB, Python, LaTeX. • You have
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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing
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magnetoencephalography (MEG) and behavioral tests Data analysis using Matlab or Python (speech-brain interactions, synchronicity measurements, connectivity measurements between sources) Presentation and publication
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Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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, Mechatronics, Data Science, or a closely related field Strong background in signal processing, measurement systems, or data analysis Programming skills in Python, MATLAB, or similar scientific computing
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, including, but not restricted to, geometry or shape optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience