109 assistant-professor-and-human-centric-computing Postdoctoral research jobs in Sweden
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical
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Do you want to help shape the future of sustainable materials? We are looking for a dedicated postdoctoral researcher to develop bio-adhesives and additives that meet both sustainability goals and
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of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to
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of the organization. Contact Main Mentor: Associate Professor Reza Hosseinpourpia, 0470-70 80 74, reza.hosseinpourpia@lnu.se Head of the department: Erika Olofsson, 0470-70 89 99, erika.olofsson@lnu.se HR partner
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design, data collation and analysis, as well as write and publish scientific papers in collaboration with the research team. The postdoc is also expected to contribute to team activities, assist in student
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schools History News 2025 School Introduction Registration Program Recordings Questions Committees Sponsors Contact Repository Lectures by topic Lectures by author Search lectures 2024 2023 2022 2021 2020
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Starting Grant from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven life science. The successful candidate will be working within
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of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to
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from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven life science. The successful candidate will be working within the development
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description