UCL Department of Electronic and Electrical Engineering


Fully funded PhD scholarship in Memristive Technologies

Duration of study: Full time - 4 years fixed term
Starting date: Flexible, available from December 2023
Application deadline: No closing date, the position will remain open until a suitable candidate is found.

Primary Supervisor: Dr Adnan Mehonic, Associate Professor in Nanoelectronics,  Department of Electronic & Electrical Engineering, University College London (UCL)

Project Description: The rapid expansion of Artificial Intelligence (AI) is hitting a critical bottleneck: sustainability. As industries like autonomous vehicles, robotics, IoT, medical technology, security, and entertainment generate an ever-increasing influx of both structured and unstructured data, the demand for computing power is skyrocketing. This demand, which doubles roughly every two to three months, exacerbates the already significant energy consumption of AI, primarily driven by data centres. These centres alone account for about 3% of global electricity use, raising serious concerns about the environmental impact and long-term viability of current AI technologies. At the same time, existing memory technologies are encountering challenges with scalability and integration. The performance gap between logic and memory components is increasingly widening, particularly in applications like low-power microcontrollers. This poses challenges for both current and future low-power applications, including edge AI.

Enter memristors, resistive devices with inherent memory functions. Since connecting the theoretical concept of memristors to physically measured devices in 2008, there has been a flurry of development, including several demonstrations of memristor-based computing systems, both digital- and analogue-based. These developments have profound implications for the future of memory technology, AI and computing at large. Specifically, memristors offer promising avenues in three key areas: on-chip memory and storage, biologically inspired computing, and general-purpose in-memory computing.

This PhD project offers a unique chance to engage with cutting-edge memristor technology. An added opportunity comes from our close partnership with Intrinsic Semiconductor Technologies Ltd, a company specialising in the commercialisation of SiOx-based memristors, who are sponsoring this scholarship. The PhD candidate will have the opportunity to interact closely with both academic and industry experts, covering an expansive range of subjects from material optimisation to device design, as well as system and algorithmic co-design. The research scope is comprehensive, encompassing experimental tasks such as fabrication, characterisation, and testing of memristive devices, along with simulation work that includes device modelling, integrated circuit design, and algorithmic development. 

Funding: This is a fully funded 4-year studentship to cover the Home student's tuition fees plus a £20,622/year stipend for living costs increasing with inflation as well as a top-up contribution towards travel and consumables. Although the fees are only covered at the Home rate, Overseas candidates are still welcome to apply. However, they would need to fund the difference between home and overseas fees themselves (e.g. through another award or self-funding) and specify this in their application.

More details about the stipend and fees can be found here: https://www.ucl.ac.uk/research-innovation-services/award-services/research-studentships/studentship-budgets.

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

Qualifications required: Candidates should have or expect to achieve an excellent degree(s) in Electronic Engineering, Physics, Computer Science or a related discipline. The ideal candidate would have experience in and passion for one or more of the following: 

  • Materials engineering, nanotechnology, device physics
  • Understanding of electrical testing and materials characterisation  
  • Machine learning

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.