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the key electromagnetic coupling effects between layers and enables fast prediction of their tunable response without relying solely on full-wave simulations. To create efficient adjoint-based optimization
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. To create efficient adjoint-based optimization methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization
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material platforms exhibiting time-varying responses. Using adjoint-based optimization and spatial structuring, to realize complex time-modulated medium dynamics with realistic material constraints 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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evaluation Sustainability analysis and life cycle assessment Uncertainty-based investment pathway modelling Multi-criteria decision making approaches and optimization System dynamics modelling Energy system
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approaches and optimization System dynamics modelling Energy system resilience and risk assessment The research will heavily involve mathematical model development and the use of specialised software
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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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) in computer science, mathematics or statistics, with an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization
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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