34 condition-monitoring-machine-learning Postdoctoral positions at Nature Careers in Denmark
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
comprehensive quantitative evidence and understanding of their capacity and cost-effectiveness for carbon sequestration under varying conditions. You will be part of a large international research project focused
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qualifications: Experience with GHG flux measurements (eddy covariance, chambers) or nutrient flux monitoring. Skills in process-based modelling or ecosystem resilience assessment. Teaching and supervision
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
The Section for Software Engineering and Computing Systems, at the Department of Electrical and Computer Engineering (ECE), invites applicants for a two-year postdoctoral position within the area of
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, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research potential at the international level
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kinase modulators. Integration of gut microbiome and skin omics data: The focus will be on the intestinal microbiome's role in inflammatory diseases. Stool samples from psoriasis patients with conditions
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Source (ESS), Sweden, the European Molecular Biology Laboratory (EMBL), Institut Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the
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only some of the above areas, but who are motivated to learn the remaining techniques, are also encouraged to apply. It is furthermore an advantage that the applicant Has experience with industry
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pharmacoepidemiology, pharmacogenetics, pharmacokinetics, drug-drug interactions, therapeutic drug monitoring and exposure to environmental chemicals. Specifically, the pharmacoepidemiological research group utilizes
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-treatment, operational modes, and gas variability on final CO2 purity and process stability. Collaborate with process modelers and experimentalists to align capture conditions with system design and operation