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Postdoc in eDNA technology for early detection of forest pathogens Umea Department of Forest Bioeconomy and Technology We are seeking a motivated postdoctoral researcher to develop and apply
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early drought detection” . The scholarship is full-time for two years with access on January 18, 2027, or as otherwise agreed upon. The last day to apply is Sep 15, 2026. The Department of Computing
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in defending future generation networks by: prevention of cyberthreats through anticipating and mitigating them, accurate detection of ongoing attacks with well-understood AI methods used for system
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evolving in time, with each technique contributing a noisy, partial observation through its own forward model. The work spans sequential Bayesian inference, deep state-space models, and uncertainty-aware
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Bayesian modelling methods, to investigate how Arctic plant communities and their functional composition have changed over time and in response to warming, precipitation change, and other environmental
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deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are
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labs and projects. Supervision of students in the subject area, including degree projects, may also be included. The position focuses on teaching and supervision in programming (object-oriented
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biological samples using chromatographic techniques. Integration and synthesis of previous data with newly collected data on fatty acids, cyanotoxins, and stable isotopes. Application of Bayesian
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, cyanotoxins, and stable isotopes. Application of Bayesian mixing models to investigate consumer diets and food web pathways Requirements To meet the general entry requirements you must have been awarded a
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molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see: https://www.scilifelab.se/data-driven/ddls