PhD Studentship: Physical Neuromorphic Computing: Novel Materials and Devices

University of Oxford; Oxford; On-site; GBP 19,000 - 23,000; Full time

Benefits offered by this job

Standard stipend

Job summary

The University of Oxford invites applications for a DPhil studentship focused on physics-based neuromorphic computing. The project investigates spin-wave dynamics and 2D spintronic circuits, combining experimental device development with nanofabrication, electrical and magnetic characterization, and modelling.

Supervised by Dr Safeer Chenattukuzhiyil within the MIND Research Group, the fellowship covers tuition fees and provides a standard stipend as part of the Royal Society grant.

Qualifications

• Strong analytical and problem-solving skills required.
• Experience or strong interest in experimental condensed matter physics, magnetism, spintronics or neuromorphic computing.
• Undergraduate or master's degree in physics, materials science or related discipline.

Responsibilities

• Plan and perform experimental investigations in neuromorphic computing hardware.
• Conduct nanofabrication, electrical and magnetic characterisation, and computational modelling.
• Collaborate with the MIND Research Group to advance spin-wave and 2D spintronic circuits.

Skills

Analytical skills

Problem-solving

Experimental physics

Magnetism

Education

Physics degree

Materials science degree

Tools

Nanofabrication

Electrical measurements

Job description

Overview

The DPhil project will explore next-generation neuromorphic computing technologies that exploit the natural dynamics of physical systems to perform brain-inspired information processing. The research will be undertaken within the MIND Research Group https://www.physics.ox.ac.uk/research/group/magnetism-intelligent-devices-mind at the Department of Physics, University of Oxford, under the supervision of Dr Safeer Chenattukuzhiyil. The PhD studentship is funded through the supervisor's Royal Society grant, covering tuition fees and providing a standard stipend.

Project Details

The rapid development of artificial intelligence (AI) has created an increasing demand for computing hardware capable of processing complex information with high speed and low energy consumption. Conventional AI systems rely on energy-intensive silicon processors, presenting growing challenges related to power consumption, scalability and computational efficiency. These limitations motivate the development of alternative computing architectures that exploit physical phenomena for information processing.

This DPhil project will focus on physics-based neuromorphic computing, where nonlinear interactions and collective dynamics in physical systems are harnessed to perform computation directly in hardware. The research will investigate spin-wave dynamics and two-dimensional (2D) spintronic circuits as platforms for developing compact, high-speed and energy-efficient neuromorphic devices.

The project builds on the MIND Research Group's recent work in physics-based neuromorphic computing, spanning real-time robotic control using nonlinear wave dynamics and the exploration of nanoscale spin-wave computing.

A major research direction will involve spin waves, collective excitations of magnetisation that propagate through magnetic materials. Their nonlinear dynamics, interference and interactions provide opportunities for physical reservoir computing and brain-inspired information processing. The research will investigate spin-wave-based devices and their application to computational tasks such as pattern recognition, temporal information processing and physical neural networks.

The project will also explore neuromorphic circuits based on two-dimensional van der Waals materials. These atomically thin materials provide opportunities to engineer spin transport, spin-charge interconversion and magnetic interactions within nanoscale devices. The research will investigate spintronic circuit architectures that exploit these properties to realise artificial neurons, synaptic functionalities and interconnected computing elements.

The research will combine experimental device development, nanofabrication, electrical and magnetic characterisation, and computational modelling to investigate the underlying physical mechanisms and demonstrate neuromorphic computing functionalities.

The overall objective is to develop new physical computing architectures that exploit spin dynamics and spin-dependent interactions, advancing energy-efficient neuromorphic hardware for artificial intelligence, robotics and intelligent sensing.

Person Specification

Please check whether you are eligible to apply for the University of Oxford Physics DPhil programme before applying or contacting the supervisor.

We seek a highly motivated candidate with a strong interest in experimental condensed matter physics, magnetism, spintronics, nanotechnology or neuromorphic computing. Applicants should have, or expect to obtain, a strong undergraduate or master's degree in physics, materials science or a closely related discipline.

Candidates should demonstrate strong analytical and problem-solving skills, enthusiasm for experimental research, and the ability to work independently and collaboratively. Previous experience in magnetism, spin dynamics, nanofabrication, electrical measurements, 2D materials, programming and machine learning would be advantageous. Candidates should also be able to work effectively both independently and as part of a collaborative research team and communicate scientific results clearly.

Application Procedure

The position will start in the academic year beginning in October 2027. The application portal expected to open by the end of October 2026, and application deadline is 6 January 2027.

All candidates should check their eligibility and review the application procedure before applying. For further details, please visit: https://www.physics.ox.ac.uk/research/group/magnetism-intelligent-devices-mind/join-group