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synchrotron infrastructure tools for ex-situ and in-situ experiments to acquire essential information regarding the microstructure and the physical mechanisms involved during thermomechanical loading
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parental leave, sick leave or military service. The following experience will strengthen your application: Experimental atomic physics Optics Photonics Optomechanics Nanofabrication Nanomechanics Cryogenics
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. Solutions will be developed for both casting and repair using techniques like additive manufacturing. Combining system-level thinking with tools such as thermodynamic modeling and machine learning, you will
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the development of single-cell models, machine learning approaches based on cultivation data, and the integration of metabolic models with computational fluid dynamics of bioreactors. While our team consists
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-constrained models. Currently, we are advancing the development of single-cell models, machine learning approaches based on cultivation data, and the integration of metabolic models with computational fluid
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optimization or machine learning. It is a plus if you are already an independent researcher or are growing into one. Therefore, you are required to submit a research statement where you describe not only your
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, computer science, physics, or a similar discipline. Note: Exceptions to the 3-year limit may apply in cases of parental leave, sick leave, or military service. Demonstrated knowledge of computational methods
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dynamics, and machine learning, we aim to: Uncover and rationalize the reactivity mechanisms of nanodroplets. Optimize the chemical properties of droplets through solvent engineering. Explore synergies with