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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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(LES). Strong knowledge in the analysis of large DNS and LES datasets, and the ability to use this data to develop reduced-order models for combustion simulations. Strong analytical skills and a proven
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monitoring data and new data collected within the project. Areas and time periods with different abundances of herring will be used to investigate the role of herring in the coastal ecosystem, as prey
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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of large bandgap semiconductors has been at the international forefront. More information can be found at: www.ftf.lth.se , www.nano.lu.se , https://kaw.wallenberg.org/en/research/semiconductor-bandgap-key
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develops over time, and how this development is affected by lack of mechanical stimulation, using a large animal model. The technical goal includes to develop, perform and analyse data from high resolution
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on collating and analyzing the large volumes of carbon cycle data gathered from the site to date, then preparing the resulting analyses for publication in scientific journals. Likely topics for papers include