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full professor in non-linear PDEs, you will expand and deepen already established connections to other mathematical research groups, such as numerical analysis, geometry, continuous optimization
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on testing a set of promising pre-identified catalysts in the existing experimental set-up. Based on your findings, you will optimize the catalytic systems and/or adapt the experimental plant to achieve
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-responsive proteins to develop genetic switches and circuits in therapeutically relevant bacteria. Your tasks: Use computational tools to design protein structures with desired properties Produce
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-driven discovery of new physics experiments to test quantum-gravity and observe gravitational waves (examples here and here ) Inventing state-of-the-art AI-driven exploration, optimization, and search
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optimization of molecular biological assays (e.g., LAMP, qPCR) Establishment and use of cell culture models Sample preparation (e.g., cell lysis, adaptation to amplification methods, as well as quantification
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developed in order to improve the chemical characterization of these ice-active compounds. The optimized analysis techniques will then be applied to a selection of atmospheric aerosol, cloud and precipitation
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support the development of a European energy system model by benchmarking future technologies and optimizing their representation within the FINE optimization modelling framework ( https://github.com/FZJ
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for implementations in the context of FAIR data principles, supported by further HMC computer scientists Support for the Helmholtz-wide HMC Hub Information at Forschungszentrum Jülich and in the domain of neuroscience
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05.05.2025, Wissenschaftliches Personal The Chair of Renewable and Sustainable Energy Systems (ENS) at the Technical University of Munich (TUM) deals with the modeling and optimization of energy
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to uncover new molecular strategies for safeguarding crops. Join a vibrant, interdisciplinary research environment where computational chemistry, biochemistry, molecular biology, and plant science converge