Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 4 days ago
overview of some of the computational techniques that are useful in statistics. Topics include methods of generating random variables, Monte Carlo integration and variance reduction, Monte Carlo methods in
-
Offer Description Mission: Develop and apply advanced Quantum Monte Carlo techniques to investigate the ground state properties and phase transitions in two-component bosonic gases with coherent coupling
-
University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 15 hours ago
program includes HDR for gyn a soon prostate implants and LDR for eye plaques. There are several active clinical and research programs in the areas of IMRT, SGRT, SRS, SBRT, Monte Carlo simulation, 4D
-
uncertainty and learning from new data. The course introduces the basics of Bayesian inference and Markov chain Monte Carlo methods, then shows students how to compute and make inferences for complex data
-
the predictions against a conventional AC power-flow solver.; ; 3) Couple the RECEP methodology with Monte Carlo scenario generation, including sequential simulation when chronology matters. Use GridFM for fast
-
spectroscopy, HPLC-DAD-CAD-fluorescence). • Analyze the experimental data and compare them with Monte Carlo simulations and, more generally, with data from the literature and from the group. • Write scientific
-
object reconstruction algorithms (specifically track and vertex reconstruction), particle physics data analysis, or Monte Carlo simulation of detectors are additional assets. • Have a good command of
-
systems. Familiarity with cloud computing environments (e.g., Azure, AWS or GovCloud equivalents). Introductory experience with graph‑based ML or GNNs is a plus Monte Carlo or stochastic simulation methods
-
NetworkX Introductory experience with graph‑based ML or GNNs is a plus Monte Carlo or stochastic simulation methods Synthetic data generation or simulation‑in‑the‑loop workflows Exposure to geospatial data
-
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 dimensional parameter