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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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October 1, 2025: Researcher (Post-Doc) (m/f/d) 80% position with a regular weekly working time of currently 31.6 hours (Reference number 06/2025) The employment relationship is limited to three years; a
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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Bioprogrammable Materials is looking for an enthusiastic Post-doctoral Researcher with experience in Protein Engineering. We combine synthetic biology and biomaterials to develop smart platforms for therapeutics
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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location as a Post-doctoral Researcher (f/m/d) on transdiciplinary methods in agroecological living labs The focus of the advertised position is on identifying and engaging actors and stakeholders within
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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omics, environmental, and chemical data, using machine learning and explainable AI. Depending on your background, interests, and evolving project needs, your work may focus on one of these areas or bridge
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early