Research Fellow in Planning, Optimisation And Control
Work type: Fixed Term
Division/Faculty: Melbourne School of Engineering
Department/School: School of Electrical, Mechanical and Infrastructure Engineering
Salary: $72,083 - $97,812 (Level A)
Role & Superannuation rate: Academic - Full time - 9.5% super
About University of Melbourne
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.
About Melbourne School of Engineering (MSE)
Working at MSE is exciting and fast moving. We are working hard to transform engineering and IT research and teaching, guided by MSE 2025, our ten-year strategic plan. With planned investment of $1 billion in people and infrastructure, we are creating the entrepreneurial leaders and technology of the future.
About the School of Electrical, Mechanical and Infrastructure Engineering (EMI)
We encompass the Electrical, Mechanical and Infrastructure Engineering Departments, recognising that engineered systems of present and future significance increasingly have connections to all three.
We are the oldest engineering school in Australia – initially founded in 1861 – and have evolved into a vibrant community of internationally recognised researchers focused on addressing major challenges of today and into the future.
The Department of Electrical and Electronic Engineering has four research groups in:
- Power and Energy Systems
- Control and Signal Processing
- Communications and Networks
- Electronic and Photonic Systems
Within these groupings, we have internationally recognised researchers who collaborate on challenging research problems of impact to society resulting in a fertile and supportive research environment that enables researchers to reach their full potential.
You will join a team of academic staff and postgraduate students working on problems pertaining to real-time decision-making in dynamic systems.
The research will focus on the coordination of a group of autonomous vehicles to achieve a common objective under uncertain and time varying operational considerations. The flexibility to handle different scenarios and associated mission constraints will be an integral aspect of the research.
The aim of the research is to explore and develop novel algorithms that result in real-time implementation and can predict under different time-scales and make optimal decisions under given performance metrics while satisfying hard constraints. This will involve generation of solutions that respond to rapidly changing conditions and uncertainties in the environment.
You will have an outstanding background in Engineering, Computer Science, or Applied Mathematics (or equivalent), as well as experience with the implementation of numerical methods and engineering applications of optimisation techniques (continuous and discrete) in real-time control of dynamical systems with exposure to mathematical foundations of learning, graph theory, system verification, and temporal logic.
You will be in the Department of Electrical and Electronic Engineering in close collaboration with investigators in the School of Computer and Information Systems within the Melbourne School of Engineering.
This exciting career opportunity will support you, independently and as a member of the team, to work across all four pillars of an academic career and you will have responsibility to:
- pursue internationally leading research
- deliver teaching and teaching innovation
- engage with industry and other partner institutions
- take on leadership roles within the University
To be successful in this role you will be able to demonstrate:
- PhD in Engineering, Computer Science, or Applied Mathematics, or equivalent
- quality research as evidenced by publications in leading journals and at conferences of systems and control and/or planning and optimisation
- expertise in system modelling and control and/or planning algorithms; strong interest in the application of these to address practical problems in real-time decision-making scenarios
- commitment to pursue fundamental research on problems pertaining to real-time decision making in dynamic systems
- your initiative; need for minimal supervision; and ability to prioritise tasks to meet timelines
- capacity to communicate research concepts to technical and non-technical audiences
- ability to work as part of a team that includes graduate and undergraduate students
- solid interpersonal and communication skills; ability to interact with University staff at all levels.
Additionally, your application will be highly regarded if you can also demonstrate:
- experience with the implementation of numerical methods and engineering applications of optimisation techniques in real-time control of dynamical systems
- exposure to mathematical foundations of learning, graph theory, temporal logic, system verification, and combinatorial optimisation.
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 challenging and rewarding role we’re ready to meet you.
How to Apply
Apply online, complete the application and upload your Cover Letter - addressing all the essential selection criteria; and your Resume.
While we review your application, get to know us by visiting http://www.eng.unimelb.edu.au/about/join-mse/why-join-mse
Applications close: 12 Nov 2019 11:55 PM AUS Eastern Daylight Time