246 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dip" "Dip" "Dip" Postdoctoral research jobs in Sweden
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any of: molecular simulation methods (integrators, force fields, enhanced sampling), structural biology, biophysics, or chemistry. Teaching experience is meritorious but not required * The date shown in
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clearly in an interdisciplinary environment, and work in a structured and proactive way. Awareness of diversity and equal opportunity issues, with specific focus on gender equality Great emphasis will be
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group (www.bourginelab.com ) led by Paul Bourgine. The group specializes in the production of ossicles/bone tissue that recapitulate the structure and function of skeletal bone and bone marrow. In the
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microscopy and spectroscopy to investigate their unique electronic, structural, and plasmonic properties. Project 2: Exploring the synthesis of metallene layers sandwiched between SiC and graphene
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, funded by Kempe fundation is full-time for two years with access may 2026 or by agreement. Departmental specific information The research group led by Jonas von Hofsten (https://www.umu.se/en/staff/jonas
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artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/ Duties and responsibilities The appointment as a postdoctoral
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. Information about the workplace: https://liu.se/en/organisation/liu/ifm https://liu.se/en/research/m2lab The employment This employment is a temporary contract of two years with the possibility of extension up
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research questions. Closing date for applications: March 13, 2026 Reference number: 2186-2026 URL to this page https://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8
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Science. https://doi.org/10.1007/s11625-025-01648-0 * Klein, A., Unverzagt, K., Alba, R., Donges, J.F., Hertz, T., Krueger, T., Lindkvist, E., Martin, R., Niewöhner, J., Prawitz, H., Schlüter, M., Schwarz
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models