179 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "Dr" "L2CM" positions at Leibniz
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The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for its three-year PhD program starting October 1, 2026. BIPS, a leading center for
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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compensation according to TV-L (including annual special payment) contribution to your company pension plan (VBL) on-site opportunities for health promotion How to apply and further information: We are looking
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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familiar with data analysis using programming languages like R, and/or Python. You have excellent communication skills and a willingness to collaborate across disciplines. You fit to us: if you have strong
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– company pension plan Senckenberg is committed to diversity. We benefit from the different expertise, perspectives and personalities of our staff and welcome every application from qualified candidates
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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organizational questions, please contact: Mandy Fitzpatrick, Tel. 0341- 21735-54, fitzpatrick(at)dubnow.de If you have any questions relating to the program, please contact: Prof. Dr. Jan Gerber, Tel. 0341-21735
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collaboration with the research groups of PD Dr. Florian Menzel (Johannes Gutenberg University Mainz), PD Dr. Jan Büllesbach (Technical University of Munich), and Prof. Dr. Thomas Schmitt (University of Würzburg
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learning and deep learning Excellent programming skills in Python Practical experience with PyTorch (preferred) and/or with TensorFlow, scikit-learn, and GitHub Experience with scientific experimentation and