AI-driven disaster management and resilience (PhD Scholarship)

Applications close

12 January 2024

You'll receive a stipend scholarship of $36,161 per annum, indexed annually, for a maximum period of three and a half years, which includes the possibility of 6 month extension, subject to approval.

If you're an international student, you will also receive a QUT research degree (HDR) tuition fee sponsorship.

As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.

To apply for this scholarship, you must meet the entry requirements for a Doctor of Philosophy (PhD) at QUT, including any English language requirements. You will need to be studying full-time and on a QUT campus.

Ideally you will have a:

• strong foundation in behavioural economics
• proficiency in data science techniques
• solid background in econometrics, quantitative research and statistical analysis skills
• experience with programming languages (e.g., Python, R)
• experience in agent-based modelling
• familiarity with artificial intelligence concepts and hands-on experience in AI applications
• hands-on experience in machine learning algorithms and tools
• ability to handle large datasets and database management
• hnowledge of experimental design and hypothesis testing
• good written and verbal communication skills for presenting research findings
• ability to work independently and collaborate with interdisciplinary teams
• critical thinking and real-world problem-solving capabilities.

Apply for this scholarship at the same time you apply for admission to the Doctor of Philosophy (PhD) at QUT. The project is ready to start in 2024, so apply as soon as possible.

The first step is to email Professor Benno Torgler and Jennifer Petley detailing your background and motivation for research study in this field, and include your CV.

If supported to apply, you will then submit an Expression of Interest (EOI) to the Doctor of Philosophy (PhD) following the advice at how to apply for a research degree .

Indicate your interest in this scholarship by nominating Professor Benno Torgler as your proposed principal supervisor, and in the financial details section, copy the link to this scholarship into question 2.

This project is starting in 2024, so contact us today at [email protected] to start your application, or with any questions about the project.

For question on how to apply, contact [email protected] .

This scholarship is funding research aimed at enhancing disaster management and community resilience in Queensland. The project focuses on using AI, machine learning and other advanced data science and econometric methods, to empirically map vulnerabilities, identify at-risk individuals, and improve preparedness among vulnerable cohorts.

As part of the research, you will:

• develop and implement AI-driven tools for vulnerability mapping and behavioural analysis to improve disaster preparedness and response
• integrate diverse data sets from multiple government levels to create comprehensive and accessible disaster management resources
• address communication barriers in disaster scenarios, focusing on cultural, linguistic, and cognitive challenges, using tailored AI solutions
• contribute inputs to the development of the 'Get Ready' digital tool, aiming to increase self-reliance in disaster situations.

This research is part of the Industrial Transformation Training Centre for Behavioural Insights for Technology Adoption at QUT, funded by the Australian Research Council and conducted in collaboration with the University of Queensland (UQ), the University of Western Australia (UWA) and industry partners.

The Training Centre is located within the School of Economics and Finance in the Faculty of Business and Law, at QUT's Gardens Point campus.

The Training Centre aims to share people, data, knowledge, and solutions to increase the adoption and uptake of technological innovation in Australia in health, agriculture, and cyber-physical systems. Research will focus on behavioural barriers to adoption and diffusion of innovative technologies and will address challenges at each stage of the innovation adoption process including conception and design; market translation; and evaluation of effective adoption.