PhD Studentship: Physical Neuromorphic Computing: Novel Materials and Devices
University of Oxford
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 gra...
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 gra...
Opportunity details
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 magnetisa...
Eligibility
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.
Requirements
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.
Funding and benefits
Funding eligibility: UK Students, EU Students, International Students, Self-funded Students.
How to apply
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. Person Specification Please check whether you are eligible to apply for the University of Oxford Physics DPhil programme before applying or contacting the supervisor. 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.
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Benefits
Funding eligibility: UK Students, EU Students, International Students, Self-funded Students.
Eligibility summary
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.
Requirements
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.
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