Silicon Synapses for Artificial Intelligence Hardware

About the project

Electronic devices such as computers, mobile phones and data centres account for a significant amount of the world's energy consumption. We need to invent novel technologies to deliver high-speed, low-power, and efficient computing and communication.

This PhD studentship aims to develop neuromorphic chips for artificial intelligence (AI) hardware accelerators. You will exploit the architecture of memristive technologies to deliver faster, smaller, and lower-powered AI chips than the conventional chips that gadgets currently use.

Memristive nanodevices are an emerging nanoelectronic technology with unique capabilities in mimicking the communication of neurons.

You can create a neural network by interconnecting a massive number of these devices. You’ll learn how to design and fabricate a massive array of memristive prototypes, investigate their reliability, and integrate them to build a silicon neural network.

The final objective of this project is to build an application demonstrator employing AI chips to run neuromorphic computations on a field programmable gate array (FPGA).

You will have access to our nanofabrication centre which includes a state-of-art cleanroom, materials and electrical characterisation facilities, and excellent research staff and technicians to support your research.

We will encourage you to attend international conferences in the UK and abroad to present your research work and guide you to publish your results in high-impact journals.

Sustainable Electronics Technologies (SET) research group

SET is one of the leading research groups in the UK, offering unique solutions to real-world problems by delivering efficient electronics while addressing all aspects of sustainability. Our research interests include neuromorphic computing, heterogeneous integration, and 2D material-based and wearable electronics. We have diverse expertise ranging from devices to systems, and our state-of-art research facilities and strong collaborations with industry enable us to explore new ways to innovate advanced nanoelectronics. We are seeking exceptional candidates to join our team, interested in devoting their passion to addressing some of the challenges we have identified.

Learn more about our SET research group

Dr Firman Simanjuntak MIET, MInstP, SMIEEE, FHEA

• Data storage, AI-hardware accelerator, secured hardware and sensors
• Nanoelectronics for space and nuclear environments

Entry requirements

You require one of the following qualifications in physics, engineering, materials science, electronics or chemistry:

• a 2:1 honours degree (or international equivalent)
• an MEng/MSc with first-class honours/distinction (or international equivalent)

Fees and funding

For UK students, tuition fees and a stipend of £17,668 tax-free each year for up to 3.5 years.

How to apply

Apply now

You need to:

Applications should include:

• choose programme type (Research), 2022/23, Faculty of Engineering and Physical Sciences
• choose PhD in Nanoelectronics (Full time)
• add name of the supervisor (Dr Firman Simanjuntak) in section 2
• a research proposal (1 A4 page)
• your cv (resumé)
• 2 reference letters
• degree transcripts to date

Faculty of engineering and physical sciences

Email: feps-pgr-apply@soton.ac.uk

Project leader

If you wish to discuss any details of the project informally, please contact Dr Firman Simanjuntak.

• Email: f.m.simanjuntak@soton.ac.uk

Research areas