National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

PhD Vacancy - METROLOGY AND PROCESS INTEGRATION FOR DEFECT MAPPING OF SEMICONDUCTOR MATERIALS

NPL
Teddington
8 months ago
Applications closed

Related Jobs

View all jobs

PhD Student Placement (Administrative Data Research Wales social care programme)

C++ Software Engineer - Stats/Maths

Research Assistant OR Research Associate in Machine Learning for Robotics

Lecturer in Health Data Science (Teaching and Scholarship)

Research Associate or Research Fellow In Machine Learning (2 Posts Available)

Data Scientist with PyMc, Python & Marketing Mixed Modelling

This highly innovative PhD project, led by Swansea University and based at NPL in London, aims to create new tools for analysing semiconductor wafers and devices, focusing on the latest materials like compound semiconductors. Compound semiconductors, important in the UK's semiconductor strategy, are used in various technologies like electric vehicles, sensors, and quantum technologies. They are more efficient than traditional silicon, but are sensitive to defects, which can lead to production issues and high costs.
 
The project will develop methods to inspect wafers more effectively, using machine learning to identify critical defects in the latest semiconductor materials like SiC, GaN and β-Ga2O3. These materials offer profound advantages for power devices over silicon technologies. This PhD work is critical as low production yields lead to wastage and slow market growth. The project is funded by an iCASE award to the National Physical Laboratory (NPL). The award will fund a Swansea University student to undertake a PhD at NPL’s Teddington laboratories near London.

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs Careers

Machine Learning Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

Jobs

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

Jobs

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.