PhD Studentship in Magnon Spintronics for Neuromorphic Computing
Develop next-generation brain-inspired computing using magnon-based nanoscale devices at the intersection of physics and computer science.
Best for:Best for interdisciplinary PhD candidates with a background in physics, materials science, or computer science, eager to explore cutting-edge neuromorphic computing and magnon spintronics.
Overview
This fully funded 3.5-year PhD project at The University of Manchester focuses on advancing neuromorphic computing through magnon spintronics. The successful candidate will design and optimize nanoscale devices that leverage magnons (collective magnetic excitations) as information carriers, aiming to create ultra-efficient, compact, and brain-inspired computing architectures. The project bridges condensed matter physics and computer science, offering interdisciplinary research opportunities. The candidate will work on automated design workflows, magnonic device optimization, and performance characterization, contributing to high-impact research in emerging computing technologies. The position is ideal for motivated applicants with a strong background in science or engineering and a passion for interdisciplinary collaboration.
What you'll do
- Develop automated design workflows for nanomagnetic devices by integrating micromagnetic simulations with machine learning and optimization techniques.
- Design and optimize magnonic primitives for wave-based neuromorphic computing, including programmable devices for nonlinear activation functions and linear multiply–accumulate operations.
- Quantitatively characterize magnonic device performance within neuromorphic computing architectures, evaluating metrics such as energy efficiency, thermal noise sensitivity, scalability, and computational throughput.
- Collaborate across disciplines with researchers in physics, materials science, and computer science to advance fundamental and applied research in unconventional computing.
- Contribute to high-impact research and develop advanced computational and modeling skills in emerging computing technologies.
Requirements
Degree required: At least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering discipline (e.g., physics, materials science, computer science, electrical engineering).
Degree offered: PhD
Language: English; proficiency sufficient for academic research and collaboration (no specific test score mentioned).
Instruction: English
- Strong academic background in physics, materials science, or computer science.
- Ability to perform high-level research and solve open problems in interdisciplinary fields.
- Excellent communication, documentation, and time management skills.
- Enthusiasm for interdisciplinary research and collaboration across boundaries.
- Proficiency in computational modeling and simulation techniques.
- Open to home students (UK/EU/International eligibility criteria may apply).
- No explicit age or residency restrictions mentioned beyond standard PhD eligibility.
Funding & terms
How to apply
Deadline: 2026-11-02
Applicants should contact the main supervisor, Dr William Griggs, via email at william.griggs@manchester.ac.uk. The application must include details of current level of study, academic background, relevant experience, and a paragraph explaining motivation for the PhD project. Applications are submitted through the university’s PhD application portal.
- CV
- Academic background details
- Relevant experience details
- Motivation paragraph explaining interest in the PhD project
Contact
William Griggs· Main Supervisor
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