124 data-"https:"-"https:"-"https:"-"https:"-"PSL-University" Postdoctoral positions in Denmark
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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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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publications in leading international venues. - Guiding and working with Master and Ph.D. students at ECE and collaborators as needed. More information - see the attached link or email: sshreya AT ece.au.dk
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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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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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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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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
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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 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