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methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization of performance targets such as efficiency
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optimization methods for high-dimensional inverse design, as well as develop practical expertise in prototyping and laboratory characterization. Go to the project webpage for more information What METATUNE
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functionalities while restricting control to a single, or otherwise limited, discrete set of tuning parameters, enabling practical global actuation and robust device operation. To design optical metasurfaces and
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operation. To design optical metasurfaces and material platforms exhibiting time-varying responses. Using adjoint-based optimization and spatial structuring, to realize complex time-modulated medium dynamics
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management This particular call emphasizes a knowledge of AI research, performance optimization of AI training and inference, and hands-on-experience with PyTorch or similar. This should be complemented with
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is made up of 13,000 students, 400 professors and close to 4 500 other staff members working on our vibrant campus in Espoo, Greater Helsinki, Finland. We actively work to ensure our community’s
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staff members working on our vibrant campus in Espoo, Greater Helsinki, Finland. We actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
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aims to strengthen its leading role in systems and operations research in Finland. Applications are welcome from all areas of operations research, including but not limited to optimization, mathematical
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Finland. Applications are welcome from all areas of operations research, including but not limited to optimization, mathematical programming, analytics, data-driven decision-making, stochastic modelling