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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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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 Materials Theory division, a
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design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments
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the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments. Information about the project and division
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while optimizing sequence properties. An emerging frontier focuses on designing proteins that act as templates for inorganic interfaces, forming symmetric oligomers that control inorganic material
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University (Boston, MA, USA), and the Singapore University of Technology and Design (SUTD, Singapore). The postdoc will become part of the TERANET@KTH research lab. The team will also work in close
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demands of both consumers and the food industry, plant proteins must exhibit high nutritional and functional quality, this includes optimal protein composition, a favorable amino acid profile, and
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proteins must exhibit high nutritional and functional quality, this includes optimal protein composition, a favorable amino acid profile, and functional properties such as solubility, gelling, and foaming
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of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks can now generate symmetric oligomers, cages, and backbones while optimizing sequence properties
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. Project description You will work on one or both of two major European research projects: UPPRAISE and MEDUSA. These projects aim to advance intelligent, adaptive, and sustainable industrial systems