Skyrmionic Devices for Neuromorphic Computing

Future integrated systems will comprise considerably heterogeneous/hybrid technologies both for computing and (on-chip) data storage. One of the emerging technologies that can complement CMOS technologies is spintronics. The distinct characteristic of spintronics is that information is retained and processed by utilizing the spin rather than the charge of the electrons [1]. 

A potential spin-based technology, magnetic skyrmions, has attracted extensive interest due to their unique physical characteristics. Magnetic skyrmions are nanoscale topologically stable vortex-like spin windings that are robust due to their topology and are considered promising candidates for information carriers in future computing systems. Their small size (nanoscale), robustness against material defects and low electrical currents required to manipulate them can lead to next generation ultra-dense, robust and low-power spintronic devices [2]. Skyrmions have been demonstrated experimentally at room temperature for the first time in technologically relevant multilayers [3], which opens the way for their use in novel applications [4,5]. Our team has also made significant strides in devising interconnect structures and designing neuromorphic devices using skyrmions. We are presently developing novel devices, models, and circuits towards the vision of integrating skyrmion-based computing with mainstream CMOS technologies facilitated by the UKRI grant "Skyrmionics for Neuromorphic Technologies" and our latest Horizon Europe consortium project "Skyrmionic Artificial Neural Networks" [6]. 

The main goal of this PhD project is to computationally design and explore skyrmionic devices that emulate brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and facilitate complex computations at the synapse level that can subsequently be interconnected by electrical CMOS connections for dense inter-layer connectivity in order to develop skyrmionic artificial neural networks hardware. In practice this means, exploring brain-inspired schemes promising for building energy-efficient computing hardware and developing fundamental components for skyrmion-based electronics and related compact models for circuit simulations. The project builds on recent achievements of the group [7] in this research area where novel skyrmionic devices for neural networks [8] and interconnects [9,10] were demonstrated. 

Consequently, the project aims to exploit these milestones to demonstrate one or more of the following: i) enhanced components that utilize the non-volatile nature of skyrmions (and other related topological quasiparticles) to highly improve the energy-efficiency of computing and/or data transfer, ii) circuit level models for these components that are highly scalable and require reasonable simulation times, and iii) use these components for emerging unconventional architectures beyond the Von Neumann paradigm .  

This is a interdisciplinary project spanning Brain-inspired computing, spintronics, electronics and Artificial Intelligence.

Research aiming to these objectives is expected to lead to high impact publications in both international competitive conferences and esteemed journals.

Entry requirements

The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).

Other combinations of qualifications and research or work experience may also be considered. Please fse.doctoralacademy.admissions@manchester.ac.uk to check.

How to apply

You will need to submit an online application through our website here: https://uom.link/pgr-apply

When you apply, you will be asked to upload the following supporting documents: 

• Final Transcript and certificates of all awarded university level qualifications

• Interim Transcript of any university level qualifications in progress

• CV

• You will be asked to supply contact details for two referees on the application form (please make sure that the contact email you provide is an official university/ work email address as we may need to verify the reference)

• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it.

• English Language certificate (if applicable). If you require an English qualification to study in the UK, you can apply now and send this in at a later date. 

Before you apply

We strongly recommend that you contact the main supervisor before you apply (Dr Moutafis - christoforos.moutafis@manchester.ac.uk).

Funding

At The University of Manchester, we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers.

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).