123 data-"https:"-"https:"-"https:"-"Stanford-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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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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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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Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 16 months. You can read more about career paths at DTU here . Further information
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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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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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. 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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Associations. The allowance will be agreed upon with the relevant union. The period of employment is 2 years. You can read more about career paths at DTU here . Further information Further information may be
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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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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