17 machine-learning-postdoc-"https:" "Naturalis" Postdoctoral positions at Umeå University
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-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 for complex data, including temporal data
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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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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Project Description The Department of Community Medicine and Rehabilitation is seeking a Postdoc for the
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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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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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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in