"Postdoctoral Research Assistant in Application of AI-driven Advanced In Situ Microscopy and Microanalysis of Fibres for Batteries and Photovoltaic Applications"

About the role
We are seeking a Postdoctoral Research Assistant in the Application of AI‑Driven Advanced In Situ Microscopy and Microanalysis of Fibres for Batteries and Photovoltaic Applications. This post is based at the Department of Materials, and offers the opportunity to work at the interface of materials science, AI, and energy technologies.

You will join an interdisciplinary research environment focused on the structural and chemical characterisation of fibre‑based materials under operational conditions. The role requires onsite work for the experimental aspects, with the possibility of flexible or part‑time working.

The Project
Working under the supervision of Professor Nicole Grobert, you will contribute to a collaborative research programme focused on applying AI‑driven analysis to in situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and chemical information, enabling deeper understanding of fibres used in next‑generation battery and photovoltaic applications.

You will work closely with academic collaborators and industry partners, and contribute to hypothesis testing, data interpretation, experimental development, and dissemination of results through presentations and publications.

This is a fixed-term post for 12 months (in the first instance), working full-time for 37.5 hours per week, though where possible, part-time arrangements may be considered.

About You
With a background in materials science, physics, engineering, computer science, or a closely related discipline, you will be self‑motivated and able to plan, execute, and deliver high‑quality research.

You will have (or be near completion of) a PhD/DPhil in a relevant field and possess specialist knowledge in at least one of the following:

• Advanced in situ microscopy / microanalysis
• Machine learning / AI for scientific data
• Electrochemical energy storage or photovoltaic materials

You will have experience in managing your own research, contributing to publications and presentations, and generating ideas for new research directions. Strong communication skills and the ability to collaborate effectively, both within a research group and with external partners, are essential.

Experience in independently managing a discrete research project and contributing to journal publications is desirable.

How to apply
You will be required to upload your CV and a supporting statement as part of your online application. Your supporting statement should list each of the essential and desirable selection criteria, as listed in the job description, and explain how you meet each one. CVs alone will not be considered. Please do not attach any manuscripts, papers, transcripts, mark sheets or certificates as these will not be considered as part of your application.

Only applications received online by 12.00 midday (GMT) on Wednesday 11th March 2026 can be considered. Interviews are scheduled to take place at the Department of Materials on 23 March 2026 (a week after shortlisting) and you must be available on this date, either by Teams, Zoom or in person.