13 machine-learning "https:" "https:" "https:" "https:" "Instituto de Sistemas e Robótica Porto" Postdoctoral positions at Umeå University
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also try going to the Startpage Technical details Code: 500 About http error codes Server: UMU-WEBSRV05 IP: 172.18.132.5 Time: 2025-11-14 06:08:30
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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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trustworthiness modeling on multimodal data and machine learning models. The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven
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support, among other benefits. See more information at: https://www.umu.se/en/department-of-computing-science/. You will research in collaboration with the Associate Professor Zoe Falomir. Interested
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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. Prof. Silvia Remeseiro, MTB / WCMM, via silvia.remeseiro@umu.se More information aobut the research in Remeseiro’s group is available through the following websites: https://www.umu.se/institutionen
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conducted in the SYMBIO group (https://www.umu.se/en/research/groups/symbio/), which is a very active research group conducting translational research in the medical area, with funding from e.g. The Swedish
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of the agreement on fixed-term employment as a postdoctoral fellow. More information about the group's research can be found on our website https://www.umu.se/en/research/groups/physiology-of-cortical-microcircuits
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be implemented in collaboration with other groups at Department of Molecular Biology, providing excellent opportunities for the prospective candidates to expand the professional network and acquire
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their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar