Industrial PhD Studentship in AI and Powder Metallurgy at University of Leeds University of Leeds in United Kingdom

Industrial PhD studentship in AI and Powder Metallurgy at the University of Leeds, jointly hosted with Plasee Austria. This is a fully funded PhD opportunity at the intersection of machine learning, computer vision, powder processing, and materials science, focused on developing AI-driven models to predict and optimise the flow and compaction behaviour of refractory metal powders such as Tungsten, Molybdenum, and Tantalum.

The studentship is interdisciplinary and involves the School of Computer Science and the School of Chemical and Process Engineering at Leeds, with direct industrial engagement through Plasee Austria’s R&D team. The post is announced by Arash Rabbani, Assistant Professor in Computer Science (AI for Materials).

Funding: full academic fees plus a tax-free stipend of £21,805/year for 3.5 years (EPSRC rate), plus a conference travel budget.

Eligibility: applicants should have a strong background in data science, machine vision, or a related quantitative discipline, with an interest in engineering or materials science applications. Laboratory experience is favourable. The opportunity is for UK/home-fee eligible students only.

Start date: October 2026.

How to apply: contact Arash Rabbani informally by email with your CV and a short statement of interest.