Memristive reservoirs and artificial neurons for neuromorphic computing (Ref: PH/SS-SF2/2026)

About the Project

We invite applications for self-funded PhD projects developing memristive reservoirs and artificial neurons for next-generation neuromorphic computing. The aim is to create hardware that can learn from time-varying signals efficiently, using device physics (including diffusion and stochasticity) as part of the computation.

AI is rapidly moving from the cloud to the edge (sensors, wearables, robotics and autonomous systems), where power, latency and robustness are critical. Memristive and physical reservoir approaches offer a route to ultra-low-power, fast, and adaptive computation —potentially enabling new capabilities in real-time signal processing, classification, prediction, and secure on-device intelligence.

Projects can be tailored to your background (physics, electronic engineering, materials, computer science). Possible directions include:

• Memristive reservoir computing for time-series tasks (prediction, classification, event-based sensing).
• Artificial neurons / “transneurons” and spiking dynamics for richer, brain-inspired computation.
• Stochastic memristive devices for probabilistic computing and true random number generation.
• Noise, instability and variability: modelling, mitigation strategies, and robust learning rules.
• Benchmarking and hardware–algorithm co-design (device models → circuits → systemlevel performance).

You will join a supportive research environment at Loughborough University, working with Prof. Sergey Savel’ev, building on a strong track record in memristive neuromorphic hardware, including publications in Nature Materials, Nature Electronics and Nature Communications:

• 10.1038/nmat4756
• 10.1038/s41928-018-0023-2
• 10.1038/s41467-017-00869-x
• 10.1038/ncomms11142
• 10.1038/s41467-025-62151-9
• 10.1038/s41467-023-43891-y
• 10.1126/sciadv.abl58

Name of primary supervisor/CDT lead: Sergey Saveliev S.Saveliev@lboro.ac.uk

Name of secondary supervisor: Prof. Alexander Balanov

Entry requirements: Applicants should normally have an upper second class bachelor’s degree (or equivalent qualifications/experience) in a relevant discipline and meet the University’s English language requirements. A master’s degree and experience with Python/MATLAB, modelling/simulation, or electronics/materials characterisation are desirable but not essential.

English language requirements: Applicants must meet the minimum English language requirements. Further details are available on the International website.

Bench fees required: No

Closing date of advert: 31st December 2026

Start date: February 2027, July 2027

Full-time/part-time availability: Full-time 3 years

Fee band: 2025/26 Band RB (UK £5,006, International £28,600)

How to apply: All applications should be made online. Under programme name, select Physics. Please quote the advertised reference number: PH/SS-SF2/2026 in your application. To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents. Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project. Please also ensure that you submit a one-page statement of interests (which topic(s) above and why).

Project search terms: computational physics

Email Address Sci: sci-pgr@lboro.ac.uk