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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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cooperation with your supervisors within the research program of the RTG. Your academic qualifications: Completed scientific university studies in a relevant subject of Natural Sciences and/or Engineering
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Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic Ph.D. student with a strong interest in computational microbiome research. The specific focus of the Ph.D. project will be tailored
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during your doctoral studies. Structured Doctoral Education We provide a comprehensive qualification programme to all doctoral candidates of Goethe University and support you individually to organise your
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. Competence in computer-aided methods for data analysis and modelling, e.g. with Python, advanced MS Excel Sheets, Aspen or multiphysics simulation tools. Excellent cooperation and communication skills complete
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to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component
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close collaboration within the ChemBion training group. We will provide a structured 3-year cutting-edge Ph.D. student training program in and beyond the fields mentioned above. REQUIREMENTS: We are
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Your Job: Synthesis of heterogeneous catalysts (Ni on Al2O3) and characterization involving e.g. TGA, IR, TEM, MS, BET Implementation of a reaction chamber for catalytic measurements into a laboratory PDF diffractometer, including the optimization of measurement protocols and combined mass...
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI