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on simulating nanoalloy structures to create a database for materials characterization. The main tasks include running molecular dynamics and Monte Carlo simulations to model nanoalloys under various
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. Provide insight on the appropriate use of Monte Carlo, deterministic, and AI-accelerated approaches for HTGR design, safety assessment, and operational analysis. Develop and validate a multiscale thermal
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to increase usage by the community. [1] https://doi.org/10.1039/C9SM01877H [2] https://doi.org/10.1063/1.5123683 [3] https://doi.org/10.6028/jres.123.004 key words Molecular simulation; Monte Carlo
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the development and refinement of Monte Carlo simulation generators to accurately model neutrino interactions with various target materials. Detailed comparisons of these simulations to data from existing neutrino
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to determine these materials’ chemical structure and its effect on their properties. This project will use theoretical modelling (density-functional theory and Monte Carlo calculations) to investigate
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be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
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radiation and using Monte Carlo simulation software (MCNP, GEANT4). Knowledge of multi-element analytical techniques (PIXE, XRF, ICP-MS). Valorization of Industrial Waste: Experience in developing processes
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funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The use of Monte-Carlo computational
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development (e.g. quantum Monte Carlo, neural quantum states, tensor networks, machine learning and data science, dynamical mean field theory, diagrammatic Monte Carlo, etc.) Key Responsibilities Conduct
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, including sequential Monte Carlo methods, Gaussian processes and Bayesian compressed sensing. Applicants from different backgrounds are encouraged to apply depending on the specific nature of the project