108 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "P" uni jobs at DAAD
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Description Hannover Biomedical Research School, as part of Hannover Medical School (MHH), invites applications for its three PhD programs to commence in October 2026 Our offer HBRS is one
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to such functions as movement, growth and regulation – emerge from interaction between their component parts. A distinctive feature of the CAFE-BIO programme is that a novel combination of modelling and analysis
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Latin America with the capacity
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Description Would you like to become a One Health expert in Helminthology? Would you like to work on your doctoral thesis in a structured and interdisciplinary doctoral program in Berlin? Here is
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available in the further tabs (e.g. “Application requirements”). Programme Description Erasmus+ mobility of individuals sponsors study periods and traineeships (work placements) in 33 specified Erasmus
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Sub-Saharan Africa with the capacity
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RTG3120 on Biomolecular Condensates ( https://dresdencondensates.org ). Each PhD project is part of an interdisciplinary framework that includes shared training activities, and supervision by
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hours Offer of professional training courses and measures for skill improvement Compensation according to TV-L (including annual special payment) Contribution to your company pension plan (VBL) On-site
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and oral Experience with atomistic electronic structure calculations Programming skills Advantages are: Prior knowledge of atomic and molecular physics Thorough and independent working style Knowledge
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, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate