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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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noble-metal tellurides. The researcher will work together with PhD students, postdocs, and a research engineer, to perform the experiments. Description of the work duties: to perform synthesis
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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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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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: 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
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strategies that balance the tradeoff between privacy and utility in continual, federated, and distributed settings. Your primary responsibility will be to conduct original, high-quality research in trustworthy