49 developer-"https:"-"https:"-"https:" Postdoctoral positions at Aarhus University in Denmark
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supervision experience at the BSc and MSc level Interest and experience in developing competitive national and international research applications Experience in planning and conducting molecular laboratory work
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/or large genetic datasets. This may include genetic analyses, causal inference, epidemiological analyses, and clinical prediction modelling using machine learning approaches, and development
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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-year extension. The project is fully funded by the Independent Research Fund Denmark (DFF). The main objective of this project is to develop physics-constrained, data-driven turbulence models
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. Specifically, the postdoc will develop and test up-scaled microbial electrosynthesis reactors involving advanced electrochemistry, reactor design, and scaling approaches. Expected start date and duration of
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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will be in developing new techniques for testing and verifying modern highly concurrent systems, such as weak-memory architectures and highly-distributed databases. The position is also open, to some
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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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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