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MST data, focussed on mirror alignment and optical performance validation by comparing data to Monte Carlo simulations What you bring to the table: - completed scientific university education and
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diffraction software and/or reverse Monte Carlo software. Previous beamline support experience in a neutron or synchrotron x-ray user facility. Experience collaborating with technical and scientific
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, sustainability objectives and future uncertainties into a unified decision-making framework. The candidate will develop probabilistic modelling and stress-testing approaches, including Monte Carlo simulations and
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, Monte Carlo radiative transfer calculations, and statistical analysis methods. Develop an all-sky NUV map based on the established FUV processing methodology and perform the same comparative analyses
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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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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
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structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. - ML-augmented numerical method development. - High-performance computing (HPC
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against annual fiscal year budgets. Regularly project financial outcomes by modeling revenue and spending, including conducting Monte Carlo simulations of projected fundraising, thinking strategically about
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formation and microstructural evolution by molecular dynamic, kinetic Monte Carlo, and kinetic rate theory calculations will complement the experimental findings, in order to provide an improved understanding
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, Bayesian inference, model calibration, and Markov Chain Monte Carlo methods, uncertainty quantification, statistical modelling, and Gaussian processes, machine learning for time series, sequence-to-sequence