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Congratulations and a very warm welcome to the three students who successfully applied to our internship scheme this year, seeing off over 1600 other applicants to the post.

Are you looking to get the most accurate information from your models, and deploy them with confidence? Uncertainty quantification (UQ) is a set of essential computational tools that can help make sure your models are both accurate and reliable. And while UQ can be a complex subject, it doesn't have to be overwhelming! In this blog post, we will break down how Uncertainty Quantification works by discussing the concept of propagation of uncertainty — as well as looking at some practical applications "in the wild!" using two simple uncertainty propagation methods: Monte Carlo Simulation and Polynomial Chaos.

digiLab was founded to provide top-tier data science to the engineering industries. A spinout from the University of Exeter, digiLab uses pioneering machine learning to transform the efficiency, resilience and environmental sustainability of its customers. This conversation with the Co-founders of digiLab, Dr Anhad Sandhu and Professor Tim Dodwell, explores the genesis of the company and reveals how digiLab is already optimising approaches to water treatment and nuclear decommissioning.

What is digiLab? digiLab is a data science technology company based in Exeter. Our founders have been key members of the Data Centric Engineering team at Exeter and have built a comprehensive background in industrial applications of data science. We are now using that expertise to provide high value data insights to our clients through a combination of software products and consulting services.

The UK Atomic Energy Authority (UKAEA) and digiLab today announced a five-year strategic collaboration that will develop unique “uncertainty quantification” capability, specifically targeting fusion powerplant design.