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Field
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influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
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will contribute to building stronger theoretical foundations for structural optimization, to designing new algorithms for such integer programs, and to applying structured integer programs to various
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controlled instructional gradients. Your work will include designing and optimizing experimental protocols, advancing microfluidic encapsulation methods, testing novel polymer materials, and employing cutting
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We are seeking a talented and motivated Postdoctoral Research Associate (PDRA) to join the Energy and Power Research Group for a 12-month appointment to develop, implement and test a numerical model
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is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up. The developed technologies will be
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Boltzmann method simplifies the numerical treatment of fluid flows by evolving particle distribution functions across straight lines on a computational grid, rather than evolving the trajectories of the flow
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farms at relatively close proximity can be relevant when considering their annual energy production. This project will examine the uncertainty of various types of numerical models, from fast-computing
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Earthquake Engineering and examines the dynamic and liquefaction behavior of Icelandic basalt sand, using laboratory test methods and advanced numerical techniques. The project is funded for three years by
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vegetation monitoring, and potentially numerical modelling. The project is a close collaboration with its sponsor, the Environment Agency, meaning your findings will inform future levee design, inspection, and
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sensing (e.g., PlanetScope, Sentinel-1), advanced numerical modelling (HEC-RAS, Delft-FM), and targeted field surveys to map mining intensity, simulate channel adjustment, and assess changing flood hazards