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Duration of study: Full time - 4 years fixed term
Starting date: Flexible, available from December 2025
Application deadline: deadline 28 Jan 2025. Please consult (https://ucl-epsrc-dtp.github.io/2025-26-project-catalogue/) for a specific application process.
Primary Supervisor: Dr Adnan Mehonic, Associate Professor in Nanoelectronics, Department of Electronic & Electrical Engineering, University College London (UCL)
Motivation: The growing demand for computing power is pushing global energy consumption to unsustainable levels. By 2035, sustaining current computing trends could surpass feasible energy limits, risking stagnation in areas like artificial intelligence and large-scale simulations. This PhD project offers an opportunity to be at the forefront of addressing this global challenge, rethinking computing architectures to develop sustainable, energy-efficient memory technologies.
Project Description: This PhD project focuses on advancing next-generation Resistive RAM (ReRAM) technologies, exploring both conventional memory applications and novel paradigms such as neuromorphic computing. You will tackle the technical and practical challenges preventing ReRAM’s widespread adoption, but also explore novel concepts - spanning material engineering, device integration, and system design with the ultimate goal of enabling scalable, energy-efficient solutions across diverse applications.
This is a rare chance to engage with cutting-edge memristor technology and benefit from a close collaboration with Intrinsic Semiconductor Technologies Ltd., a pioneering company commercialising SiOx-based memristors. You will benefit from a unique, multidisciplinary environment, encompassing material optimisation, device design, system integration, and algorithmic co-design. Your research will include:
- Fabrication, characterisation, and testing of memristive devices
- Simulation work, including device modelling and integrated circuit design
- Development of algorithms for novel computing applications
Funding: This is a fully funded 4-year studentship to cover the Home student's tuition fees plus a £21,237/year stipend for living costs. Full funding is available for UK students. International applicants are welcome to apply; however, funding for overseas candidates is not guaranteed (more details on: https://www.ucl.ac.uk/epsrc-doctoral-training/prospective-students/apply-ucl-epsrc-dtp-studentship)
Qualifications required:
We are looking for highly motivated candidates with:
- A strong academic record in Electronic Engineering, Physics, Computer Science, or a related discipline
- A strong interest for one or more of the following:
- Materials engineering, nanotechnology, and device physics
- Electrical testing and materials characterisation
- Machine learning and AI systems
The candidate should pass the entry requirements of PhD programme at UCL EEE: https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/electronic-and-electrical-engineering-mphil-phd
This is your opportunity to shape the future of computing while earning your PhD at a globally recognised institution. For specific questions you can contact adnan.mehonic.09@ucl.ac.uk; please use the email title: PhD Opportunity in Memristive Technology – Enquiry
How to apply: Applications must be made using the UCL online application system by using the UCL postgraduate study application form. Please mark it to the attention of Dr Adnan Mehonic.
Equality, diversity, and inclusion: Our research is driven forward by talented researchers and PhD students who come from countries and backgrounds across the globe. We therefore strongly encourage applications from underrepresented backgrounds in engineering, such as women, ethnic minorities, or people with disabilities– EEE is a great place for you to study! We will make reasonable adjustments at interview and/or in the position as requested.
Contact: For informal inquiries please contact Dr Adnan Mehonic (adnan.mehonic.09@ucl.ac.uk ) who will be happy to answer any queries about the project.