PhD: ML-Driven Materials for Fusion Structural Integrity

NLP PEOPLE; Teddington; On-site; GBP 60,000 - 90,000; Full time

Job summary

NPL in the UK seeks a senior researcher to advance machine learning and NLP methods for structural integrity assessment in fusion-relevant materials. The role combines experimental work with ML to predict material performance and extend component lifetimes.

Based across University of Surrey, Guildford, and NPL in Teddington, this post involves working with DSIT, accessing national datasets, and delivering scalable, transferable ML approaches for engineering challenges.

Qualifications

• Bachelor's degree (Upper Second) required; Master's degree preferred.
• Discipline: engineering, material sciences, mechanical engineering, physics or related.

Skills

Machine Learning

NLP

Data analysis

Education

Master's degree preferred

Upper Second Bachelor's degree required

Tools

Python

TensorFlow

PyTorch

Job description

NPL in the UK seeks a senior researcher to advance machine learning and NLP methods for structural integrity assessment in fusion-relevant materials. The role combines experimental work with ML to predict material performance and extend component lifetimes.

Based across University of Surrey, Guildford, and NPL in Teddington, this post involves working with DSIT, accessing national datasets, and delivering scalable, transferable ML approaches for engineering challenges.