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. The Subatech Laboratory developed over the past ten years some expertise in the simulation of nuclear reactor cores using Monte-Carlo approaches with a special interest in decay heat calculations. The Cocodrilo
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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-performance computing, astrophysical data analysis, statistical methods including Markov Chain Monte Carlo, and working both independently and in collaborative research environments. Colourbox via Unsplash
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. Knowledge of statistical analysis and Markov Chain Monte Carlo Experience with machine learning Ability to work independently and in collaborations Language requirement: Good oral and written communication
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coupled nuclear engineering problems, using techniques such as (but not limited to) molecular dynamics, computational fluid dynamics, activation decay codes, kinetic Monte Carlo codes, particle transport
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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contact information for at least two (2) professionals in the field who can provide letters of recommendation. Applications must be submitted at this link: https://apply.interfolio.com/178857 . Applications
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varying material properties. The resulting response will be analyzed using techniques such as Monte Carlo simulations. Identifying the variability of the model parameters using Bayesian inference
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skills with Python. Desirable qualifications: Previous experiences with kinetic Monte Carlo. Previous experience with machine learning applications in molecular modelling, including experience with
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Kinetics models - from simplified Point Kinetics to more detailed Space Kinetics approaches – and by integrating high-fidelity neutron physics calculations performed by Monte Carlo methods to generate