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, data structures, and data analysis. The research team develops algorithms and data structures with provable guarantees, by leveraging theoretical insights to obtain state-of-the-art practical algorithms
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experience with Python Knowledge of energy systems analysis and modelling, AI and machine learning for data analysis. Experience with the modelling tool OSeMOSYS for energy and CLEWs application Awareness
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accordingly. To connect local material properties to macroscale asphalt pavement performance, you will employ multi-scale numerical modelling based on the Finite Element method. This project is a collaboration
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5 Dec 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Mathematics » Algebra Mathematics » Geometry Mathematics » Mathematical analysis Researcher Profile
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to fair pricing Design and analysis of decentralized energy markets The doctoral candidate will join the research group of Assistant Prof. Giuseppe Belgioioso . Supervision: Assistant Prof. Giuseppe
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to modern laboratories, advanced analysis tools, and strong industrial partnerships within KTH’s leading research environment Supervision: Weihong Yang, Docent, weihong@kth.se and Pär Jönsson, Prof. parj
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experimental platform and combine it with continuum modeling of complex materials and machine-learning-based analysis methods to understand and predict biofilm structure and growth. Supervision: Shervin Bagheri
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system control, particularly in vehicles or buildings. Experience with field measurements, data collection, and energy use analysis. Knowledge of simulation and modeling of energy systems, preferably using
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description The subject field encompasses the development of knowledge, principles, methods, and tools that support the analysis and governance of complex socio-technical systems and their long-term development
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microscope building and operation, photo-switching studies. Microscopy-based assays and image analysis will be an integral part of the project as well as imaging on state-of-the-art super-resolution