155 web-programmer-developer-"LIST" "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
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Your Job: Chromatography modeling, while crucial for modern bipporcess development, still heavily relies on empirical determination of key model parameters. By combining protein structure
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the inductive heating of heterogeneous catalysts as an integral advantage. Your focus will be on the investigation, development, and optimization of this new process in a continuously operated reaction
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Your Job: Development, preparation, and characterization of state-of-the-art and novel catalysts for polymer recycling towards hydrogen carrier molecules Characterization of polymer thin films
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analyses, you will develop import scenarios for Germany, visualize your results, and derive recommendations for future import strategies. Throughout the project, you will receive guidance and support from
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close to full-time, allow you to tailor your working hours to suit your individual needs. For more information, visit: https://go.fzj.de/near-full-time KNOWLEDGE & FURTHER TRAINING: Your development is
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Service makes it easier for international employees to get started CAREER CENTER: You will receive explicit support with regard to your career development opportunities: https://go.fzj.de/careercenter FIXED
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detail: Identification of novel electrolyte components (conductive salts, solvents/co solvents and functional additives) and their optimal compositions for the development of advanced non aqueous aprotic
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program in the field of process engineering, environmental engineering, biotechnology, chemistry, or a related field Interest in process simulation Excellent organizational skills Ability to show initiative
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of holiday with us KNOWLEDGE & FURTHER TRAINING: Your further development is important to us – we provide targeted and individual support, e.g. through training and networking opportunities specifically
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devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training methodologies for machine learning systems