258 data-"https:" "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions in Denmark
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well as interviews with the students and their families. Further information Applicants are encouraged to contact project manager Laura Gilliam (lagi@edu.au.dk ) to obtain the full project description. The position
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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biogeochemical modelling and data-driven machine learning approaches at an ecosystem scale to improve our understanding of the fate of nitrogen fertilizers applied to agricultural soils. This understanding will be
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researcher, you will work closely with an interdisciplinary team of quantum physicists, photonics engineers, and information theorists. Your key responsibilities will include: Conducting experimental research
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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measurements A good understanding of advanced physiological techniques Experience with enzymatic in vitro assays and plant x climate interactions Experience in complex data handling and statistical analysis
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the Division for Geomagnetism and Geospace, an internationally leading research environment with strong expertise in space physics, geomagnetism, and data analysis. This position is connected with the ERC
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. The pharmacoepidemiological research group utilizes the world-class Danish registries as well as international data sources to assess pharmacological questions in large populations. The environmental medicine group studies
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and applying genetic and genomic approaches to biodiversity research. This includes integrating environmental DNA (eDNA) and molecular tools with ecological data to enhance our ability to assess
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be developed and implemented in the GEOS-Chem chemical transport model, coupled to the Community Earth System Model. Standardized large wildfire events will be simulated based on historical data and