Research Supervisor Connect

Neuromorphic AI

Summary

This project involves complex systems modelling of neuromorphic atomic switch networks to emulate emergent brain-like features of adaptive, deep-learning for application to Artificial Intelligence (AI).

Supervisor

Professor Zdenka Kuncic.

Research location

School of Physics

Program type

PHD

Synopsis

 This project aims to emulate brain-like features that are critical for adaptive learning, such as memory and plasticity, from a complex network of atomic switches. The project involves developing and optimising a mathematical and computational model of various experimental systems comprised of self-assembled networks of nanowires. The experimental nanowire switch networks exhibit neuromorphic features in response to electrical stimulation.  The complex systems model will be used to gain deeper insights into these neuromorphic switch networks, including the dependence of spatial-temporal collective nonlinear dynamics on network connectivity and scale. Although the project primarily involves computational modelling, it also involves close collaboration with experimental researchers in Japan and the model will be used to guide the development of optimised neuromorphic switch networks, potentially leading to a next-generation artificial intelligence (AI) system.

Additional information

This project involves collaboration with the International Center for Materials Nanoarchitectonics (MANA) at the National Institute for Materials Science (NIMS), Tsukuba, Japan. The successful PhD candidate will have the opportunity of a visiting scholarship at NIMS-MANA.

HDR Inherent Requirements

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:

- Confidential disclosure and registration of a disability that may hinder your performance in your degree;
- Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
- Ability to perform independently and/or with minimal supervision;
- Ability to undertake certain physical tasks (e.g. heavy lifting);
- Ability to undertake observatory, sensory and communication tasks;
- Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
- Ability to work in confined spaces or at heights;
- Ability to operate heavy machinery (e.g. farming equipment);
- Hold or acquire an Australian driver’s licence;
- Hold a current scuba diving license;
- Hold a current Working with Children Check;
- Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Opportunity ID

The opportunity ID for this research opportunity is 2213