29 structural-engineering-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" uni jobs at Forschungszentrum Jülich
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: Required Qualifications: Very good performance in your Master’s studies in Electrical Engineering, Computer Science, Geoinformatics, Energy Systems, or related field Very good knowledge of Machine Learning
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de/welcome FLEXIBILITY: Flexible working time
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, intermediate products, and finished products based on, for example, historical trade data ( https://www.cepii.fr/CEPII/en/bdd_modele/bdd_modele_item.asp?id=37 ) Analysis of historical developments in material
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proactively maintaining the relevant websites Your Profile: Completed master`s degree in natural sciences, engineering or information technology, preferably with a PhD Experience with the structures
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well as spectroscopic methods to determine their composition, structure, and oxidation-state distribution. In addition, variable temperature and pressure studies will be carried out to probe their structural stability
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master`s degree in natural sciences, engineering or information technology, preferably with a PhD Experience with the structures of the EUROfusion consortium is advantageous Experience in the field
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, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following tasks: You will work together
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are building a lab-on-chip system where structured “microbial arenas” are created and manipulated in real time. Microbes and tailor-made microgels are observed and moved by laser-based optical tweezers in a
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processes based on CO2 and other carbon-rich waste streams enable net-zero CO2-conversions into valuable chemicals. This project aims to design, integrate and optimize metabolic pathways in an engineered C