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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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Technology Laboratory (QTL) division of the Microtechnology and Nanoscience (MC2) department, working in a large team of PhDs, postdocs and researchers. About the research We are seeking PhD students to work
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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fast-paced research environment, a structured and organized approach is highly valued. You will work in a team of researchers from diverse backgrounds, including PhD students and postdocs, and should
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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areas: 1) Public health problems 2) Incentives and organization within healthcare 3) Design of healthcare systems in terms of efficiency and distribution 4) Economic evaluations of health interventions
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: Intermediate Storage and Distribution for Maritime and Land Transport”, funded by Energimyndigheten. The project addresses key challenges in enabling large-scale compressed gaseous hydrogen infrastructure in
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations