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National Physical Laboratory (NPL)

PhD: Integrating Experimental Advances with Machine Learning for Digital Transformation in Materials

Teddington
£21.8k/yr
Posted 1 day ago
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About the Role

Location: University of Surrey, Guildford and NPL, Teddington

The UK is leading the global fight against climate change, with a commitment to achieve net-zero greenhouse gas emissions by 2050. A cornerstone of this strategy is the development of nuclear fusion, a promising clean energy source. However, realising fusion energy requires overcoming significant engineering challenges, particularly ensuring the structural integrity of fusion materials and components in extreme environments. Effective materials performance evaluation is essential for structural integrity management, enabling the extension of lifetimes and the reduction of maintenance costs. This project addresses these challenges by combining experimental breakthroughs with advanced machine learning (ML) to transform how structural integrity is assessed and predicted. While ML holds transformative potential, challenges such as resistance to new methods and the reliance on high-quality datasets must be overcome. Partnering with the National Physical Laboratory ensures access to critical datasets, cutting-edge facilities, and industrial validation. This collaboration enhances data reliability and fosters confidence in ML-powered solutions. By delivering robust, scalable, and transferable approaches, this project advances structural integrity management, supports the UK’s fusion energy ambitions, and provides innovative tools for sustainable technologies across engineering sectors.

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Funding Notes: Home fees equivalent of £5,238, and UKRI standard stipend of £21,805 for 2026-27, and research training support grant of £4,000 over the funding period.


About You

Applicants should have (or expect to obtain by the start date) at least an Upper Second Bachelor’s degree, and preferably a Master’s degree, in an appropriate discipline (e.g. engineering, material sciences, mechanical engineering, physics, chemistry or a related subject)

Link to apply: https://www.findaphd.com/phds/project/integrating-experimental-advances-with-machine-learning-for-digital-transformation-in-materials-performance-evaluation-and-structural-integrity/?p195099


About Us

The National Physical Laboratory (NPL) is a world-leading centre of excellence that provides cutting-edge measurement science, engineering and technology to underpin prosperity and quality of life in the UK. Find out more about what it is like working here - The measure of us - Overview

NPL and DSIT have strong commitments to diversity and equality of opportunity, and welcome applications from candidates irrespective of their background, gender, race, sexual orientation, religion, or age, providing they meet the required criteria. Applications from women, disabled and black, Asian and minority ethnic candidates in particular are encouraged. All disabled candidates (as defined by the Equality Act 2010) who satisfy the minimum criteria for the role will be guaranteed an interview under the Disability Confident Scheme.

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At NPL, we believe our success is a result of the diversity and talent of our people. We strive to nurture and respect individuals to ensure everyone feels valued by treating everyone on the basis of their own individual merits and abilities regardless of their own or perceived identity, as part of our commitment to diversity & inclusion, we ensure we’re creating an environment where all our colleagues feel supported and welcome. More about this on our Diversity & Inclusion page.

We are committed to the health and well-being of our employees. Flexible working and social activities are embedded in our culture to create a positive work-life balance, along with a broad range of rewards, benefits and recognition. Our values are at the heart of what we do, and they shape the way we interact, develop our people and celebrate success. To ensure everyone has an equal chance, we’re always willing to make reasonable adjustments to the recruitment process. If you would like to discuss, please contact us.

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Skills

Machine Learning
Materials Science
Structural Integrity Management
Experimental Research
Data Analysis
Nuclear Fusion
Mechanical Engineering
Physics
Chemistry

Location

Teddington, England, United Kingdom

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