Discovery Early Career Researcher Award - Grant ID: DE240101190

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DE240101190

Funding Status
Active

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Funded Activity Summary

Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capable of quantifying inaccuracies. Scientists and decision-makers will benefit from the ability to obtain timely, reliable insights for challenging applications.

Funded Activity Details

Start Date: 01-01-2024

End Date: 31-12-2026

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $451,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Statistical data science | Computational statistics | Statistics | Statistical theory

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Computational statistics | Expanding Knowledge In the Mathematical Sciences | Statistical data science | Statistical theory | Statistics

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