Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
on simulating nanoalloy structures to create a database for materials characterization. The main tasks include running molecular dynamics and Monte Carlo simulations to model nanoalloys under various
-
. Provide insight on the appropriate use of Monte Carlo, deterministic, and AI-accelerated approaches for HTGR design, safety assessment, and operational analysis. Develop and validate a multiscale thermal
-
conferimento di n. 1 incarico di ricerca scientifica di Fascia 1 presso la Sezione di Roma dell’INFN - 12 mesi Where to apply Website https://www.ac.infn.it/ Requirements Additional Information Eligibility
-
combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
-
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
-
combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
-
amplitude estimation to improve extreme adaptive optics (XAO) performance of the Extremely Large Telescope’s future Planetary Camera and Spectrograph instrument Compare via Monte Carlo models viable wavefront
-
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
-
to determine these materials’ chemical structure and its effect on their properties. This project will use theoretical modelling (density-functional theory and Monte Carlo calculations) to investigate
-
radiation and using Monte Carlo simulation software (MCNP, GEANT4). Knowledge of multi-element analytical techniques (PIXE, XRF, ICP-MS). Valorization of Industrial Waste: Experience in developing processes