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to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component
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. Such superlattices are the key element for many prospective applications, including light-emitting diodes (LEDs) and electro-optical modulators. Time-resolved X-ray diffraction. In this project, we want to understand
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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are studied. The applicant must have a master or equivalent degree in physics or astrophysics. Expertise with spectroscopic data analysis and a background in star formation studies are useful. The position will
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relevant to the Institute's research; experience with quantitative research methods and statistical analysis, ability to work independently and in interdisciplinary teams, with excellent organizational and
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development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering experiments. For more information, visit our web page: https://www.soft
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Astronomy. Main projects include eROSITA, ATHENA, H.E.S.S., CTAO, eXTP, THESEUS, HERMES and GIFTS. We conduct data analysis and modelling of multi-wavelength observations of galactic compact sources