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of BRIGTH and ensures effective development and implementation of strain design procedures in our design-build-test-learn workflow using big data and data science. The Analytics team is part of
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publication record in the relevant area. Proven ability to conduct independent research and analyse experimental data. Experience in teaching at the undergraduate level. For non-Scandinavian candidates
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hyperspectral imaging data as input. We want to enable real-time prediction and assessment of the materials’ physicochemical behaviour and performance characteristics. This position is one out of two postdoc
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Job Description The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark
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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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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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, 4000 Roskilde. The affiliation will be with Aarhus University, Department of Environmental Science. More information can be obtained from Alexandre Anesio(Head of Section), ama@envs.au.dk , and Carsten
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to determine instability growth rates and connect experimental data to theoretical models. The candidate will contribute to the design and implementation of key components, including helicon antennas for plasma
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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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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