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Field
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, laboratory analyses and numerical modelling approaches. You will collect samples from outcrops and core repositories, perform lipid biomarker extractions and GC-based analyses to identify organic compounds and
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activity focuses on understanding the scalar sector of the Standard Model by considering both the Higgs boson and Nambu-Goldstone states. The selected candidate will be able to contribute, in particular
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environments, with applications to both the Solar System and rocky exoplanets. The successful candidate will develop theoretical and numerical models that connect the physical and chemical evolution of planetary
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models for the fire resistance of LSF walls, including the development of machine learning models, experimental testing, and numerical simulations, within the project “FireLSF – Development of Predictive
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physiology, animal models of cancer and cachexia, imaging, histological analyses, and other mechanistic or translational approaches. · Contribute to the development, optimization, and validation
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morphodynamic numerical modeling. Field data collection and analysis of nearshore dynamics. Design and analysis of flood control infrastructure. Nature-based flood mitigation solutions. Flood risk and hazard
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geothermal projects lead to significant seismic activity?’ The project combines laboratory experiments, geophysical field monitoring and numerical reservoir modelling. This postdoctoral researcher will work
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Applications are invited for a Postdoctoral Research Associate in transportation data science and statistical modelling, based in the Centre for Transport Engineering and Modelling (CTEM
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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Eligibility criteria The candidate must have a strong background in materials physics, atomistic simulation, or numerical modeling. Experience in molecular dynamics and handling force fields is required