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, computer science, or similar topics. Experience with optimization, data-driven or machine-learning skills are meritorious. The candidate must have the PhD degree in hand before enrollment, but it is not required
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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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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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. 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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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
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. Collaborate within academia and with external partners, contributing to the fusion research community. Potentially teach undergraduate or master’s courses and supervise master’s or PhD students. This position