883 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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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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/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
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. Please visit the following homepage for more information on the Department: https://www.slu.se/en/about-slu/organisation/departments/Animal-Biosciences/ Read more about our benefits and what it is like
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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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programs for both Swedish and international students. Read more at https://www.biology.lu.se/ . Find more reasons why Lund University and the Faculty of Science are right for you here and here , and learn
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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
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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: March 31, 2026 Reference number: 2313-2026 URL to this page https://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=10058&rmlang=UK
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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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June 2026, UFV-PA 2026/581 Where to apply Website https://uu.varbi.com/en/what:job/jobID:908266/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent