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Quantum diffusive memristors for neuromorphic computations

   School of Science

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  Prof S Saveliev, Dr A Balanov  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The resistance of a memristor depends on history of voltage applied to or electrical current flowing through the device. As the result, while operating the memristor usually switches between its low- and high-resistive states. If a classical memristor connected in parallel to a capacitor and in series in a load resistor, it can behave like an artificial neuron converting a voltage signal to current spikes. This proposal will study how the spiking behaviour of an artificial neuron will change if we consider quantum switching between different memristor states. The research will contribute towards development of functional elements for quantum brain-inspired computations.

Loughborough University is a top-ten rated university in England for research intensity (REF, 2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. Find out more


Electrical circuits with volatile memristor devices show a rich dynamical behaviour, including hysteresis in current voltage characteristics, self-sustained spiking oscillations and multistability. All these dynamical features make such circuits very similar to the neurons in the biological brain cortex, where the information processing involves current spike exchange between neurons. One of the most promising artificial neurons is based on the so-called diffusive memristors, where switching between different resistive states is determined by distribution of nanoparticles between memristor terminals. The project will be related to the modelling of the circuits involving the memristors with quantum diffusion of nanoparticles.

This project will be an important step towards understanding of if/how quantum phenomena can be utilised in AI systems and quantum neuromorphic computers.

Find out more:

D. Marković, and Julie Grollier, Quantum neuromorphic computing, Appl. Phys. Lett. 117, 150501 (2020)

Entry requirements for United Kingdom

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Mathematics, Physics, or closely related subject. A relevant Master’s degree and/or solid experience in one or more of the following will be desirable: numerical methods for large set of ordinary and/or stochastic differential equations, computer programming skills (MATLAB, Python), experience in numerical analysis of quantum systems. Applicants must have an enthusiastic attitude towards innovation and commitment to develop high-quality research.

Please see the programme website for international entry requirements by country.

English language requirements

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


All applications should be made online at Under programme name, select Physics.

Please quote reference number: SS/PH/2022

Funding Notes

Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects within the School. Funding decisions will not be confirmed until early 2022. The studentship is for three years and provides a tax-free stipend of £15,609 per annum for the duration of the studentship plus tuition fees at the UK rate. International (including EU) students may apply however the total value of the studentship will cover the International Tuition Fee Only.
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