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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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, the focus will be on implementing inverse design, optimization, and/or machine learning for designing and optimizing devices in integrated photonics, which will be subsequently fabricated and tested by our
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methodologies for optimally allocating these services based on the characteristics, availability, and operating conditions of different energy resources The research will primarily focus on improving system
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experimental research focused on downstream processing and refinery technologies for fermentation-based or microbial biomasses. Optimize microbial protein flavor and functionality while ensuring economic
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real