RMIT CIAIRI PHD/MBR Scholarships in AI Techniques for Emergency Management and Critical Infrastructure.
The RMIT Centre for Industrial AI Research and Innovation (CIAIRI), is seeking talented and motivated PhD and Master’s by Research candidates to join the CSIRO Next Generation Graduates program awarded to CIAIRI.
This program will produce a cohort of graduates with much-needed skills in Artificial Intelligence to support critical infrastructure and community safety. The Next Generation Graduates Program is a cohort-based, industry driven, multi-disciplinary graduate training program that aims to equip students with skill sets that are key to boost breakthrough innovation in the exciting fields of AI and other emerging technologies.
There are several projects in this program as described below, each with an associated industry partner. There is an industry placement component with the partner as part of the candidature, and a generous, above market average scholarship.
Scholarship value – PhD $53,000 per year for 3.5 years and MBR $53,000 per year for 2 years. Plus another $5000 bonus allowance. Tax free!
Eligibility – applicants must be domestic students as per the Higher Education Support Act at the time of award. Domestic students include:
- Australian citizens
- Australian permanent residents
- a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time
- a New Zealand citizen.
How to apply – Applicants are invited to directly submit their curriculum vitae (CV) and a cover letter outlining their motivation, how they meet the prerequisites for the project and fit for the role, via email to the contact listed for the relevant project.
Projects, Prerequisites and Contacts below:
1. PhD Position in Using behavioural insights in the modelling of self-evacuation from bushfire events – in collaboration with Strahan Research.
This project will develop Artificial Intelligence models that mimic human behaviour during bushfires. You will extend research on human decision-making and behaviour in response to bushfire threat to develop effective AI and agent-based models of mobility to improve safety of evacuations.
The PhD will work on: Understanding and modelling individual and household decision-making and behaviour in bushfire events, including representation of self-evacuation archetypes; Designing AI computational models to simulate human behaviour during events; and Create Explainable AI systems to support evaluation and validation of bushfire evacuation strategies.
Prerequisites
Tertiary degree in related field and experience in software development with modern programming languages such as Java; C++; Scala.
Contact: Dr. Sebastian Rodriguez <sebastian.rodriguez@rmit.edu.au>
2. PhD Position in Artificial Intelligence for Timber Structure Design Optimisation – in collaboration with Pryda (https://pryda.com.au).
This project aims to tackle the critical challenges faced by the Australian timber frame sector including timber structure design, cost efficiency, resource usage, sustainability, and productivity, through developing advanced Artificial Intelligence (Al) and digital technologies. We encourage motivated students passionate about integrating advanced technology into structural engineering to apply.
Prerequisites
First-class honours in Civil Engineering, Computer Science, or similar fields from a recognised institution; Prior research experience in Al, machine learning, or structural engineering; publications in relevant fields will be an advantage. Experience with data analysis and statistical software.
Contact: Associate Prof. Lei Hou <lei.hou@rmit.edu.au>
3. PHD Position in the Use of Evacuation Simulation Tools in Real-time using Al – in collaboration with GHD.
This project will undertake a research project (within an international development team) using Al techniques to allow for the use of the evacuation simulation platform WUI-NITY, in real-time (i.e. during an actual bushfire event). In this project,Al will be used to identify scenario(s) from a database of pre-run simulation results that best fit current fire conditions to then predict future evacuation outcomes and identify potential traffic management strategies in real-time. The Al approach that is adopted will be identified by the student and then agreed upon with their supervisory team. The student will work closely with GHD and their new Al Centre of Excellence on this project, alongside the RMIT supervisors. The outcome will represent a step-change in modelling capabilities – advancing research capacity to explore evacuation dynamics and, potentially, laying a benchmark for practice going forward.
Prerequisites
Experience of development with at least one modern object-oriented development language: either Java, C# or C++, and degree in a related field.
Contact: Associate Prof. Erica Kuligowski <erica.kuligowski@rmit.edu.au>
4. Master’s by Research Position in Using AI to Map Social Vulnerabilities in Bushfire-affected Areas – in collaboration with GHD
This project will undertake a research project (within an international team) using machine learning to further enhance the vulnerability mapping function of the evacuation simulation platform, WUI-NITY, for bushfire-prone areas. At present, this simulation platform incorporates only a simplistic function to assess community vulnerability that is based primarily on evacuation time and the number of people still left in the affected area. A new vulnerability function will identify and map the levels of vulnerability of selected areas for a range of bushfire scenarios, incorporating current research into vulnerability metrics and providing researchers and practitioners with insights into the mitigation strategies they should prioritise to reduce vulnerability in affected areas.
Prerequisites
Proficiency with data analysis and statistical processing, and some experience of development with at least one modern development language: either Java, C#, C++ or Python, and a degree in a related field.
Contact: Associate Prof. Erica Kuligowski <erica.kuligowski@rmit.edu.au>