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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
on monitoring biodiversity, water resources and management, and carbon dynamics across several newly implemented, restored, or preserved wetland showcases in rural, peri-urban, and urban areas of Europe, spanning
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or equivalent) Research plan – description of current and future research plans Complete publication list Separate reprints particularly relevant papers. The deadline for applications is 1 June 2025, 23:59 GMT +1
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perfluorinated alkyl substances (PFAS) from waste management facilities. Foreign and Danish studies have shown that landfills and wastewater treatment plants are important sources of PFAS to the aquatic
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project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting
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competitive national and international research applications Experience in managing large datasets and modelling Experience in planning and conducting laboratory work Experience in planning and conducting field
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, or equivalent research background. Your background might include experience in areas such as: Large datasets management, preferably with modeling, statistical or LCA background Uncertainty analysis, statistical
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Are you motivated to turn advanced research into real-world solutions for climate-smart sustainable soil management? Join us at Aarhus University's Department of Agroecology as a postdoctoral
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Are you motivated to turn advanced research into real-world solutions for climate-smart sustainable soil management? Join us at Aarhus University's Department of Agroecology as a postdoctoral
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knowledge in neurobiology is desirable Track record of international mobility is highly valued Publication record is necessary Collaboration and project management experience is required Ability in fellowship
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operators, transformers/LLM) and NN training. Strong Python programming skills (as a plus: C++ or Julia) and knowledge of scientific computing libraries (numpy, scipy, JAX…) and machine learning libraries