"Postdoctoral Research Associate (Level A)"

About the opportunity

The School of Project Management at the University of Sydney is a leading hub for interdisciplinary research at the intersection of engineering, systems thinking, and organisational studies. As governments and industries worldwide invest trillions into large-scale transport, energy, defence, and technology initiatives, there is a critical need for new AI-enabled approaches to understand, predict, and improve the behaviour of these multi-billion-dollar megaprojects.

We are seeking a Postdoctoral Research Associate (Level A) to join an ambitious research program advancing AI-enabled decision-making dynamics in future megaprojects. The successful candidate will work with Dr. Wanchun Liu, Senior Lecturer and Australian Research Council Discovery Early Career Researcher Award (DECRA) Fellow, whose work spans advanced AI, cyber-physical systems, and the science of large-scale infrastructure and organisational complexity.

This research stream goes beyond solving isolated engineering problems. It seeks to establish a new generation of AI-powered frameworks capable of transforming how large organisations design, govern, and execute complex programs-ranging from national infrastructure to major technological rollouts. The project focuses on developing intelligent decision architectures, predictive analytics, and adaptive computational models that can operate in dynamic, uncertain, and high-stakes project environments.

The appointee will conduct original research, publish in leading journals and conferences, collaborate with industry and government partners, and contribute to major competitive funding initiatives. This is a unique opportunity to help shape a new frontier of AI-enabled megaproject research with real-world national and global impact.

Your key responsibilities will be to:

• conduct high-quality, original research on AI-enabled decision-making dynamics in complex, large-scale project systems
• develop formal, computational, or simulation-based models to study how decisions, incentives, feedback, and learning evolve over time in megaproject environments
• investigate system-level mechanisms, including stability, path dependence, lock-in, and performance or creativity degradation in socio-technical decision processes
• design and implement quantitative methods (for example, learning-based, network-based, or agent-based approaches) to analyse dynamic decision behaviour, rather than focusing solely on predictive or optimisation performance
• prepare and submit high-quality manuscripts to leading interdisciplinary and high-impact journals
• contribute to competitive research proposals and broader research impact activities.
• collaborate closely with researchers across engineering, project management, economics, and AI to address ill-defined, cross-disciplinary research questions
• supervise or mentor research students, where appropriate.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. In this context, we are seeking a Postdoctoral Research Associate in AI-enabled decision-making dynamics in future megaprojects with strong quantitative skills and an interest in understanding how decision-making processes evolve, stabilise, or degrade in complex socio-technical systems.

Essential qualifications and experience

• a PhD (or near completion) in one of the following fields (or a closely related discipline):
  • Computer Science, Artificial Intelligence, or Machine Learning
  • Economics or Econometrics (particularly applied micro, behavioural, or decision-focused modelling)
  • Applied Mathematics, Operations Research, or Statistics
  • Systems Engineering, Decision Science, or Complex Systems.
• demonstrated research capability in one or more of the following areas:
  • quantitative modelling of dynamic or adaptive systems
  • reinforcement learning, multi-agent systems, network or graph-based models
  • simulation of complex socio-technical or organisational systems
  • causal inference, econometric analysis, or formal decision modelling
  • optimisation, stochastic modelling, or control-inspired analytical approaches
• strong programming skills in Python and familiarity with modern computational toolchains
• a clear interest in theoretical or system-level questions, such as how incentives, feedback, evaluation criteria, or AI support tools shape long-term decision behaviour
• excellent written and verbal communication skills, with the ability to engage across disciplinary boundaries
• the ability to work both independently and collaboratively within an interdisciplinary research environment.

Desirable

• experience with advanced AI or machine-learning methods beyond standard predictive modelling
• prior exposure to qualitative or mixed-methods research, or willingness to engage with non-technical perspectives
• interest or experience in infrastructure delivery, organisational systems, or large-scale project environments.

Work Rights
Visa sponsorship is available for this appointment.

Pre-employment checks
Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

How to apply
Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.

For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.

For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Chris Masaoka, Recruitment Operations by email to recruitment.sea@sydney.edu.au.

Click to view the Position Description for this role.

Applications Close
Sunday 05 April 2026 11:59 PM