274 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" Postdoctoral positions in Sweden
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods
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are widely used in a variety of projects, in particular in the EU funded projects AVENGERS (which is coordinated by Lund University, https://avengers-project.eu) and IM4CA (https://im4ca.eu). Work duties The
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
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Home EMA The European Magnetism Association Executive Board General Council Documents Membership EMA news Communication Social Networks Mailing Event Dissemination Rules All news EMA editorials Obituaries Awards beyond EMA Materials 2023 survey Commitments Young EMA EMA Awards Technical...
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promote sustainable agriculture. More about the Department: https://www.slu.se/en/departments/ecology/ More about working work at SLU: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala, Sweden
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international research collaborations to generate cutting-edge research and outreach to further ecology as science and promote sustainable agriculture. More about the Department: https://www.slu.se/en/departments
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on the long term globally 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