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collaborating with industry partners on a project aimed at developing kinetic Monte Carlo simulations to model epitaxial growth processes. The goal is to control and optimise the growth of nanoscale structures
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real-time data analysis and interpretation code. Build a connection between experimental data, analytical solution and Monte Carlo X-ray scattering simulations. In collaboration with ALS Photon Science
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significant contributions to the experimental work, taking on responsibilities for data analysis. This includes developing relevant data analysis techniques and software, as well as conducting Monte Carlo
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developing relevant data analysis techniques and software, as well as conducting Monte Carlo simulations of detector responses using the GEANT4 framework. The candidate will be strongly encouraged to actively
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and familiarity with Bayesian Inference and Markov chain Monte Carlo. Please upload your CV, a cover letter (maximum 2 pages) and names and emails of three contactable referees. The School
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., exact diagonalization, Krylov subspace methods, quantum Monte-Carlo, tensor network methods. Demonstrated programming skills using relevant languages, e.g., C/C++, Python, Matlab, Julia, and familiarity
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neutrons (and effectiveness of detector shielding) will be studied using MCNP6 and GEANT4 Monte Carlo simulations. The overall experimental goal is to unfold the runaway electron spectrum as a function of