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mindset and intellectual curiosity to strengthen and complement the research profile of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund
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of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University. The research group, which is headed by Jakob Nordström , is also active
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Description of the workplace The PhD student will be working in the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University
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focuses on developing advanced optimization and control strategies (e.g., deep reinforcement learning) for large-scale sustainable grids, to enhance overall system stability, flexibility, and resilience
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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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learning, optimization algorithms, and interoperability frameworks for optimal energy management across Europe. KTH leads technological landscape analysis, multi-energy investment planning tool development
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sustainability but also pose serious challenges in ensuring their reliability and fairness. Addressing these societal-scale challenges demands for novel optimization and control methodologies that can meet their
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albuminuria levels. Risk-based clinical decision support: Developing tools and frameworks to guide decisions using individualized risk prediction metrics to optimize patient care. Identifying and addressing
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optimizing electrolyte systems (including hybrid solvents, functional additives, and water-in-salt electrolytes), and investigating the electrochemical performances of designed aqueous batteries. The main