257 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " Postdoctoral positions in Sweden
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Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work
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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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Postdoctoral Position and Postdoctoral Fellowship (2yrs) in Intracellular Host-Pathogen Interactions
proteomics analyses. APPLICATION PROCEDURE Please note that the application procedures differ between the two postdoc projects. More information about the application procedures is provided here: https
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and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
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April 1st 2026 or by agreement. For more details about the position and the application procedure see: https://www.umu.se/en/work-with-us/open-positions/postdoctor-2-years-in-organic-electronics-with
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Website https://umu.varbi.com/en/what:job/jobID:899404/type:job/where:39/apply:1 Requirements Additional Information Work Location(s) Number of offers available1Company/InstituteUmeå
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their doctoral degree earlier may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances
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and written) are a requirement. For more information, see: https://streuff.weebly.com and https://www.carltryggersstiftelse.se Application The application should state the above reference (CTS25) and
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. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/ Duties
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. Documented knowledge and experience in computational metabolomics, computational biostatistics, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related