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systems”, coordinated by Prof. Dr. Marco Salvalaglio and Prof. Dr. Axel Voigt and funded by the German Research Foundation (DFG). The core activities will focus on the investigation of disordered correlated
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to fulfill the aims of this projects, computational chemistry aspects of the project will be co-supervised by Dr. Mehedi Davari at the IPB (Projects: Leibniz Institute of Plant Biochemistry English ) and
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English ) and Chemical synthesis by Professor Martin Weissenborn at MLU ( AG Prof. Weissenborn ) Our Research Training Group BEyond AMphiphilicity – BEAM – combines highly original science and research
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theoretical tools for their description (C). Tasks for project RTG2861-A4 (Principal Investigator: Prof. Dr. Stefan Kaskel, Chair of Inorganic Chemistry I, Research area A): Research topic: Microstructured PCL
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theoretical tools for their description (C). Tasks for project RTG2861-A4 (Principal Investigator: Prof. Dr. Stefan Kaskel, Chair of Inorganic Chemistry I, Research area A): Research topicMicrostructured PCL
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. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Application procedure The application should be marked with Ref [Project_ID] and be written in English. The
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information about the position please contact: Prof. Denis SCUTO Your profile Master's degree in Digital History, Data Science, Historical Migration Studies, Digital Humanities, or a related discipline Proven
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materials (natural and synthetic fibers, yarns and fabrics) which are highly anisotropic and non-linear. Furthermore, the dynamics of high-speed manufacturing processes need to be included in the modelling
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materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH (AMO ) in Aachen, Forschungszentrum Jülich (FZJ ), Max Planck
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning