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A leading research university in the UK is seeking an experienced Research Associate in Thin Film Transistor Devices. This full-time role, based at the King’s Buildings Campus, involves developing electronic devices using thin film technologies for innovative memory applications. The successful candidate will have a PhD in a relevant field and proven experience in cleanroom fabrication processes, working within a pioneering programme aimed at advancing AI hardware solutions.
Grade UE07: £41,064-£48,822 per annum
School of Engineering, College of Science & Engineering
Institute for Integrated Micro and Nano Systems (IMNS)
Full Time: 35 hours per week
Fixed Term: contract up to 24 months
We are looking for an experienced Research Associate in Thin Film Transistor Devices. The position will be based at the King’s Buildings Campus and will commence as soon as possible.
Our ambition is to push the frontiers of electronics through emerging nanotechnologies, disrupting current ways of thinking by innovating advanced energy‑efficient Hardware solutions for AI and the new age of electronics.
To realise this vision, we are seeking exceptional candidates to join our team, interested in devoting their passion for addressing some of the challenges we have identified.
This post will involve the development of electronic devices based on thin film technologies for novel memory‑in‑computing and emerging memory applications. These include designing device architectures and material stacks with standard cleanroom processes (lithography, magnetron sputtering, ALD, etc), analytical and morphological characterisation of developed films (such as XPS, SEM and AFM) as well as electrical characterisation of fabricated devices.
This position is affiliated with the prestigious Royal Academy of Engineering Chair in Emerging Technologies held by Regius Chair of Engineering Prof Prodromakis, Director of the Centre for Electronics Frontiers. The appointee will support the delivery of the vision of this 10‑year programme that aspires to develop AI Hardware solutions for Lifelong Learning applications.