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approach that includes cross-section calculations, the development of Monte Carlo codes, and the advancement of the NanOx model for biological dose prediction. As part of a collaboration with the University
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statistical physics at Department for materials research in extreme conditions. . The appointed researcher will join the project team and contribute to the development of the Diagrammatic Monte Carlo X
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period of up to 12 months in the first instance, with the possibility of an extension, subject to funding. The project entails the development of a kinetic Monte Carlo (KMC) framework for the simulation
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collaboration, dedicated to the direct detection of dark matter. They will contribute to various activities including data taking, data analysis, and Monte Carlo simulations. The candidate will be involved in
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following: (a). Analytical methods, e.g. mean-field theory, quantum many-body theory, field-theoretical approaches. (b). Numerical many-body methods, such as exact diagonalization (ED), quantum Monte Carlo
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skills 6. Competence in spoken and written English 7. Ability to work in a team Desirable criteria 1. Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group
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English Ability to work in a team Desirable criteria Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group or Truncated Conformal Space Approach Knowledge of quantum field
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physics. Develop and refine Monte Carlo event generator tools. Perform phenomenological studies for current and future collider facilities (such as RHIC, LHC and EIC). Collaborate with faculty and students
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
Monte Carlo charged particle simulations to model energy deposition and generation of secondary particles, and collaborate with a team of researchers to explore heating, melting, vaporization, and general
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, renormalization group techniques or Monte-Carlo methods. Investigating topological properties of magnetic quantum states such as fractional quasiparticle excitations in spin liquids. Transferring the obtained