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from the ATLAS experiment. These measurements improve the understanding of perturbative QCD in the Standard Model, are sensitive to the proton PDFs, and constitute a valuable input for improving
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via theory, numerical models, and observations (particularly satellite altimetry). This includes analytic and numerical investigations of submesoscale turbulence and wave-turbulence interactions, and
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include validation of the proposed models, quantitative performance evaluation, and comparison with other sensing techniques such as cameras and LiDAR. A strong interest in wireless systems, signal
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
record of scientific productivity and innovation. Ideal applicants will have expertise in virology, molecular biology, gene delivery, immune cell therapy, computational modeling, immunology, bioengineering
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SPECIFICS The Postdoctoral Scholar will be part of a team that is advancing the integrated movement modeling framework and is making them accessible to ecologists. The Postdoctoral Scholar will help develop
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mitigation strategies, such as selective yaw control and power down-regulation of wind turbines. Use experimental, field, and numerical data to validate, improve, and develop fast analytical wake models
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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for a research engineer with the experience and knowledge to independently perform experimental work related to human cell reprogramming and to conduct both in vitro and in vivo studies in animal models
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the formation of wrinkles • conducting experiments • analysing results • developing a model to report on the results • publishing one or more articles on the analysis of data collected during the project. It is
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of an Experienced Researcher with 12,50% of the regular working time is to be filled as soon as possible, for the project Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models