172 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Forschungszentrum Jülich
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structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de
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fossil fuel based ones. Applying a Choice of Technology Model to a database of processes used to produce various chemical products in different world regions the objective estimate impact of changes in
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Your Job: The electrocatalytic interface engineering department, led by Prof. Dr.-Ing. Simon Thiele focuses on the manufacturing, analysis, and simulation of functional materials to find an optimal
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interdisciplinary and exciting field of neuromorphic and brain-inspired computing, collaborating with physicists, neuroscientists, materials scientists, and engineers FLEXIBILITY: Flexible working arrangements
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experiments. Close collaboration with chemists, engineers, and data scientists will enable the creation of a robust, high-throughput framework for future catalyst and layer development and efficient
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) Intense interaction with consortium Your Profile: Master and PhD degree in materials science, physics, chemistry, informatics, machine learning, energy technology or related subjects Prior experience in
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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
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establishing the institute Writing of third-party funding grants and support thereof Your Profile: Master`s degree with PhD in physics, chemistry, materials science, chemical engineering, or a related discipline
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reports Develop and apply software tools Document software and data according to the FAIR data principles Your Profile: Master`s degree in astronomy, physics, computer science or equivalent degree Solid
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high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling