CSIRO Industry PhD Scholarship: Collaborative cyber defence: reconciling mixed-mode decisions in human-AI teams

Funding and duration

four year scholarship package totalling approximately $48,000 per annum tax exempt (2026 rate); four-year scholarship and research training program.

Project overview

Project title

Collaborative cyber defence: reconciling mixed-mode decisions in human-AI teams

Project description

This Project explores mixed-mode decision-making in defensive cyber operations, with a focus on resolving conflicts between operators and AI agents, as well as among AI agents themselves. The expected outcomes include methods for reconciling decision inconsistencies within human-AI cyber teams, thereby improving collaborative incident response. Ultimately, this research aims to enhance mixed-mode collaborative defence capabilities, contributing to more resilient and adaptive cyber operations.

Supervisory team

University

Name of university supervisor | Salil Kanhere

Name of university | University of New South Wales

Email address | salil.kanhere@unsw.edu.au

Faculty | Engineering

CSIRO

Name of CSIRO supervisor | Mohan Baruwal Chhetri

Email address | mohan.baruwalchhetri@csiro.au

CSIRO Research Unit | Technology

Industry

Name of industry supervisor | Anton V. Uzunov

Name of business/organisation | Defence Science and Technology Group

Email address | anton.uzunov@defence.gov.au

Further details

Primary location of student | University of New South Wales, High Street, Kensington NSW 2052, Australia

Industry engagement component location | DSTG Eveleigh, Australian Technology Park, Data 61 Building, Suite 101, 13 Garden Street, Eveleigh NSW 2015, Australia DSTG Fairbairn, David Warren Building, 24 Scherger Drive, Canberra Airport ACT 2609, Australia DSTG Edinburgh, Third Avenue, Edinburgh SA 5111, Australia

Other locations | CSIRO Marsfield, 26 Pembroke Road, Marsfield NSW 2122, Australia

Ideal student skillset | The candidate must be an Australian Citizen and have the following skillsets: Technical Expertise: Practical experience and/or understanding of AI or multi-agent systems, distributed systems, self-adaptive systems, and AI reasoning techniques (rule-based, Bayesian, counter-factual).Research and Personal Skills: A strong interest in multi-disciplinary research, excellent teamwork abilities, a solid work ethic, and the capacity to work independently. Cybersecurity Knowledge: A demonstrated passion for cybersecurity and its real-world applications.

Application close date | Open until position filled

Apply | Contact Salil Kanhere