We are looking for a PhD candidate from the fields of operations research or systems science, or related fields such as computer science. Applicants must hold an Australian citizenship at the time of application.
We welcome expressions of interest (EOIs) from 1st May 2021 until the position is filled. We will review EOIs upon arrival and fill the position accordingly. The commencement of enrolment will be discussed with the successful candidate.
We offer an opportunity to work on this interdisciplinary research project in partnership with the Defence Science and Technology Group (DSTG), and a prestigious top-up scholarship of AUD $15,000 per year for up to 3.5 years.
PhD Research Project Description
The design and operations of large-scale capability systems (e.g. health, urban planning, emergency management, defence force) constitute complex decision problems with high levels of uncertainty involving multiple, interdependent factors.
One key factor focuses on evaluating the impact of new, emerging technologies under different and evolving operational conditions. In such contexts, decision making can be supported and enhanced by building quantitative simulation models representing experts' assumptions about the causal relationships and feedback effects in the system. Once developed, the simulation model(s) can help assess the potential contributions of new technologies to both strategic and operational effectiveness, identify unintended consequences, assess systemic risks, and support planning to exploit opportunities and mitigate risks.
This interdisciplinary research project aims to develop a model-based learning methodology to support decision makers with the analytical methods needed to address these challenges.
The development and use of a library of system dynamics simulation models, within a multi-method research design, will be central to the research. The simulation models will enable evaluation of a range of different technological concepts across a set of selected strategic and operational contexts.
A multi-case study approach will be used to support the development and validation of the methodology, with one case study focused on tactical land warfare. In addition, the modelling methodology will provide the design principles to guide the use of system dynamics models within a multi-method approach to analyse the broader class of problems encompassing the evaluation of emerging technologies under uncertainty.
Required Skills and Experiences
A Bachelor of system science, operations research, systems engineering, or related fields such as computer science, applied mathematics, other engineering majors, etc.
Demonstrated experience with computational analysis and statistical analysis
Self-motivation and enthusiasm to work in an inter-disciplinary area and cross-institutional research environment
Ability to work in a team and strive for research excellence
Excellent oral and written communication skills.
Qualification of a first-class honours or equivalent (e.g. Bachelor + Master by Research/Master by Coursework + publications)
Demonstrated background in simulation modelling (in general) and system dynamics (in particular).
The joint supervision team will consist of two leading academics and an analyst from the Defence Science and Technology Group: Professor Shayne Gary, Associate Professor Sondoss Elsawah and Dr Matthew Richmond. The supervisory team possesses a strong research track record of applying systems modelling across different applications, including defence, as well as extensive experience in applying operations analysis and modelling support to future land force design (i.e. in direct support of Army Headquarters). The team has extensive experience disseminating research results via peer-reviewed publications and will guide and support the candidate to access relevant subject matter experts, as well as to publish and develop a solid basis for future career development.
To apply, please send the following documents in an email to: email@example.com.
A recent CV
An expression of interest document explaining why you are interested in this specific opportunity and how you meet the required and desired skills and experience. It would be helpful to include information about the relevant courses/training you have completed.
If you have any questions, please contact Associate Professor Sondoss Elsawah.