Integrated Micro and Nano Systems
Advanced electronic/optoelectronic technologies designed to allow stable, intimate integration with living organisms will accelerate progress in biomedical research; they will also serve as the foundations for new approaches in monitoring and treating diseases.
Research Theme
Novel Computing and Beyond-CMOS hardware
Aim
To develop reconfigurable magnetic reservoirs that exploit the nonlinear dynamics of advanced magnetic materials for ultra-low-power, real-time in-memory computing and classification of complex sensor signals, targeting practical edge applications including biosensing and sonar technologies.
Objectives
- Develop and characterise magnetic reservoirs based on advanced magnetic materials and topological spin textures, prioritising material platforms that minimise reliance on critical raw materials and heavy metals to support scalable, sustainable and supply-chain-resilient technologies.
- Design reconfigurable in-memory computing architectures in which magnetic states and device parameters can be tuned to optimise temporal information processing, establishing quantitative relationships between material properties, spin dynamics and computational performance.
- Demonstrate real-time processing of complex temporal sensor signals across complementary applications: (i) electrocardiogram (ECG) heartbeat classification as an accessible biosensing benchmark; and (ii) sonar digital signal processing, developed with KAON Ltd, targeting relevant tasks such as signal/event detection, classification and temporal discrimination under challenging or noisy conditions.
- Optimise magnetic reservoirs for practical edge applications using multiscale modelling, and machine-learning-assisted design, targeting low energy consumption compact hardware and high classification performance relative to conventional computing approaches.
Description
Artificial intelligence is increasingly moving from large computing centres towards sensors and edge devices, where conventional hardware faces severe constraints in energy consumption, size and data movement. Reservoir computing offers a radically different approach: the nonlinear dynamics of a physical system can transform and process time-dependent information directly, potentially reducing reliance on energy-intensive digital computation.
This project will develop reconfigurable magnetic reservoirs using advanced magnetic materials and topological spin textures, such as skyrmions, whose nonlinear and history-dependent dynamics provide a natural platform for in-memory computing. Through multiscale simulations combined with machine learning, the student will establish how material properties, magnetic interactions and device architecture determine computational performance, while prioritising materials with reduced dependence on critical raw materials and heavy metals.
The technology will be evaluated through two complementary demonstrators. Heartbeat classification from electrocardiogram (ECG) signals will provide an accessible biosensing benchmark. In collaboration with KAON Ltd, a second demonstrator will investigate magnetic-reservoir approaches to sonar digital signal processing, including detection, classification and temporal discrimination of signals under challenging conditions.
The project will establish a pathway towards compact, adaptive and ultra-low-power intelligent sensing hardware, with applications spanning wearable monitoring, sonar processing and autonomous defence systems where energy, latency and computational resources are constrained.
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree.
Further information on English language requirements for EU/Overseas applicants.
This position is fully funded.
This PhD project will develop sustainable, bio-based gas sensors for applications in environmental monitoring, healthcare and smart packaging. The research will explore renewable and low-impact materials, including bio-derived substrates, functional polymers and carbon-based sensing layers, combined with scalable printing and coating techniques. The student will investigate how material composition, device architecture and processing determine sensitivity, selectivity and stability when detecting gases such as ammonia, nitrogen dioxide and volatile organic compounds.
A central focus will be the complete life cycle of the sensors. The student will design devices for disassembly, recovery and recycling, investigating how substrates, electrodes and sensing materials can be separated and reused or safely biodegraded at the end of use. Working with collaborators in polymer chemistry and recycling, the project will connect device performance with biodegradation and recyclability assessments, establishing practical design principles for high-performance sensors that minimise resource consumption and electronic waste.
The successful candidates will join our team, which includes researchers from the Institute for Integrated Micro and Nano Systems, the School of Chemistry, and the wider College of Science and Engineering.
Before you apply: We strongly recommend that you contact the supervisor for this project before you apply.
https://eng.ed.ac.uk/sustainable-printable-electronics-research-group
- a 2:1 undergraduate degree (or equivalent).
- applicant's must meet the University’s English language requirements.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere
Funding may be available to Home students on a competitive basis. Candidates are invited to discuss potential funding opportunities.
Developing renewable energy solutions that can be rapidly implemented in the market using eco-friendly materials and manufacturing methods is crucial. Among various renewable technologies, photovoltaics have significant potential to support climate change mitigation. Organic photovoltaics (OPVs) have recently attracted considerable attention due to a new family of semiconductors that enable highly efficient light harvesting in both indoor and outdoor environments. Additionally, OPVs offer a low carbon footprint and high recyclability potential.
However, a current limitation is the use of toxic solvents and materials in manufacturing. Most organic electronic devices require halogenated and non-halogenated aromatic solvents, which are often carcinogenic or toxic to human reproductive systems and harm the environment. For large-scale production and commercialization, this is a critical issue.
This project aims to enhance the performance of OPVs through engineering strategies, eliminate the use of toxic materials and implement methods to enhance their stability. In addition, thin films and OPVs will be evaluated with a series of optoelectronic and morphological characterisation tools.
The PhD candidate will be supervised by Dr Julianna Panidi (School of Engineering) and Dr Yue Hu (School of Chemistry).
The successful candidates will join our team, which includes researchers from the Institute for Integrated Micro and Nano Systems, the School of Chemistry, and the wider College of Science and Engineering.
Eligibility
- a 2:1 undergraduate degree (or equivalent).
- applicant's must meet the University’s English language requirements.
Before you apply: We strongly recommend that you contact the supervisor for this project before you apply.
https://eng.ed.ac.uk/sustainable-printable-electronics-research-group
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.
Funding may be available to Home students on a competitive basis. Candidates are invited to discuss potential funding opportunities.