3D Heterogeneous Integration of 2D Electronic Materials for Neuromorphic Computing

This projects aims to develop two-dimensional (2D) materials, such as MoS2, which are atomically thin and offer a unique solution for neuromorphic computing hardware, in a 3D system where data processing and storage are unified within the artificial synapses and neurons to realize complex functions such as perception and learning.

The rapid march of information technology towards the big data era demands highly dense information bit storage and fast computing electronics. This has imposed a bottleneck for the conventional Von Neumann computing architecture where the separation of the memory and central processing units has significantly limited the performance. 

Inspired by the human brain where the data processing and storage are unified within the synapses and neurons to realize complex functions such as perception, learning, and memory, several electronic devices that could implement such biological synapse characteristics have been proposed and developed.

Two-dimensional (2D) materials, such as MoS2 and WSe2 are atomically thin and offer a unique solution for neuromorphic computing hardware. Their intrinsic dangling bond-free structure allows them to maintain their electronic properties even at atomic scales make them ideal for dense and efficient stacking in 3D architectures. This integration can dramatically enhance both the performance and energy efficiency of neuromorphic systems, positioning them as a strong alternative to conventional computing architectures.

At Southampton we have recently developed and fabricated memristor systems which show many of the brains functions while at the same time having reliability of more than 1 billion switches. It is the objective of the PhD project to develop novel materials, devices, and architecture to allow integration of Graphene and electro-deposited or chemical vapor deposited 2D materials into a 3D system. This project combines chemistry, electronics, and computer science, and requires a logical mind and strong experimental skills.

Co-supervisor: Dr Ruomeng Huang (https://www.southampton.ac.uk/people/5x9wls/doctor-ruomeng-huang)

Entry requirements

A UK 2:1 honours degree, or its international equivalent, in one of the following:

• engineering
• chemistry
• physics
• material science

How to apply 3D heterogeneous integration of 2D electronic materials for neuromorphic computing nearmejobs.eu University of Southampton

You need to:

• choose programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• choose the relevant PhD in Engineering
• add name of the supervisor in section 2

Applications should include:

• personal statement
• your CV (resumé)
• 2 academic references
• degree transcripts to date