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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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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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Position Description: Apply Position Description The Physics Department of Ariel University, Israel, invites applications for a postdoctoral; position in lattice quantum field theory/quantum Monte-Carlo
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Ph.D. in Physics or a closely related field is required. Candidates with a strong background in quantum many-body theory and experiences in quantum Monte Carlo and tensor network methods are encouraged
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simulation or machine learning of soft and biological matter, e.g. Monte Carlo, molecular dynamics and finite element computer simulations. Origins of life research involving topology and chirality
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engineering, such as neutronics, nuclear reactor physics and designs, nuclear power system, Monte Carlo methods as well as some required undergraduate mechanical engineering core courses, supervise master and
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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 brain regulates its blood supply in health but also in diseases such as Alzheimer’s. The main focus of this project will be using theoretical methods such as Monte Carlos simulations to generate
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materials science • Extensive knowledge of computer-based modelling and simulation methods in materials science of metals, e. g. Calphad method, precipitation simulation, cellular automata, kinetic Monte