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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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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 2 months ago
programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in
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(command line-based) and scripting languages such as R, Python, Unix/shell Excellent command of written and spoken English Ability to work both independently and in a collaborative, interdisciplinary
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systems and basic knowledge in information theory ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in AI‑based attack models and security research The following points
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a related field ▪ Strong knowledge in wireless communication systems, signal processing, or radar systems ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in hands
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skills. Experience with programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above
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skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX or PyTorch, is a plus. In addition to above-average interest in the topic
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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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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