The University of Melbourne is consistently ranked among the leading universities in the world, we are globally engaged; comprehensive; research-intensive; and committed to responding to the major challenges of our time.
You will join a team of academic staff and postgraduate students within the Department of Electrical and Electronic Engineering. In these roles you will have the opportunity to collaborate with leading computer vision and machine learning researchers at the University of Adelaide, as well as industry partners.
There are two research themes that will be explored in the domain of trusted autonomous systems, and the appointees will work on one of these areas:
- Developing approaches that can solve constrained optimisation approaches multi-objective optimisation problems, particularly under uncertainty.
Whilst the initial phase of research will focus on algorithms that manage the exploration-exploitation tradeoff in a single vehicle, the subsequent extensions will consider multiple vehicles sharing information to reduce the uncertainty in the decision-making process.
- The hierarchy of control, sensing, classification and symbolic planning modules that constitute the software in an autonomous system.
This research theme will investigate the development of codesign and verification tools that allow the overall autonomous system behaviour to be guaranteed at a certain level of performance.
In addition to preparing technical reports, research publications, and computer simulations, the research fellow(s) will present to our industry partner and a multi-disciplinary group of collaborators.
To successfully secure one of these research fellow opportunities, you will demonstrate an outstanding background in Engineering, Applied Mathematics or Computer Science. You will additional have experience in engineering applications of real-time control of dynamical systems and/or exposure to mathematical foundations of learning and optimisation.
Your achievement and/or expertise in relation to the following will be readily confirmed:
- PhD in Engineering or Applied Mathematics, or a closely related discipline
- record of quality research as evidenced by research publications in leading journals and at conferences of systems and control, and optimisation
- expertise in system modelling and control and a strong interest in the application of these to address practical problems in real-time decision-making
- programming skills in multiple languages including C/C++ and MATLAB, and capability of working with simulators to deliver tangible outcomes
- capacity to communicate research concepts to technical and non-technical audiences
- taking initiative; working with minimal supervision; ability to prioritise tasks to achieve project objectives within timelines
- Excellent social skills, including ability to work well with internal and external partners (academic, administrative and support staff) in a courteous manner.
Additionally, it is desirable (but not essential) if you are also able to demonstrate experience with:
- implementation of numerical methods and engineering applications of optimisation techniques in real-time control of dynamical systems
- delivering tangible results with real-world relevance in research projects
You will be supported to both independently and as a member of the team, work on all four pillars of your academic career by:
- pursuing internationally leading research
- teaching and teaching-innovation
- engagement with industry and partner institutions
- and taking on leadership roles within the University
What we offer you
We offer flexibility, whatever that may mean for you. Many of our benefit programs and onsite amenities are aimed at supporting you - including generous leave, child care subsidies, discounted parking, medical and health care. We offer extensive opportunities for personal and professional development, and we'll support you in doing what you love.
We seek to increase the diversity of our workforce and the representation of all members of our community that have been traditionally under-represented.
If you're curious, motivated and ready to undertake a meaningful and rewarding role we're ready to meet you.
How to Apply
Apply online, complete the application and upload your Cover Letter - addressing all selection criteria; and your Resume.
Please note that this project commences in early 2020, as such we will be reviewing applications on an ongoing basis prior to the closing date.
While we review your application, get to know us by visiting http://www.eng.unimelb.edu.au/about/join-mse/why-join-mse