The ideal candidate will have a great attitude, enjoy working in a collaborative team and will be someone who thrives in an environment where we are committed to working with industry leaders to respond to the challenges they face.

  • A PhD in Engineering, Computer Science or Applied Mathematics
  • Expert knowledge in the theory of system modelling and control
  • Prior experience in the application of autonomous systems for real time decision making scenarios
  • Track record of quality research as evidence in publications in leading conferences and journals
  • Outstanding ability in analysing data, problem solving and maintaining accurate data
  • Experienced in analysing data and maintaining accurate research

If you’re curious, motivated and ready to leap into a career at a world leading university, we’re ready to open our doors to you.

Apply here.

Salary: $69,148 – $93,830 p.a. plus 9.5% superannuation
Close date: 10 Sept 2018

Position Description and Selection Criteria

Download File 0045812_13 Aug 2018.pdf

A great discovery, opinions, and remembering Bruce Francis

Yesterday I discovered a page maintained by Oded Goldreich where a set of ideas, essays and opinions are posted. It is absolutely great. I particularly enjoyed:

Also, I just realised Bruce Francis has passed away. I never knew him personally and my interactions with him were from a distance. But he always seemed like a great academic with a keen mind and I have enjoyed listening to his presentations and reading his technical and nontechnical writing. I recommend checking out his work and his opinions.



Open PhD Positions

Applications are invited for two PhD scholarships in the areas of (1) real-time decision making for autonomous systems in uncertain environments, (2) secure networked control systems.

The work will be based within the Control and Signal Processing (CSP) Lab, MIDAS Lab, the Department of Electrical and Electronic Engineering, the University of Melbourne. The student will be supervised by Dr Iman Shames (see for more information) and co-supervised by another MIDAS Lab faculty member.

The ideal candidate should have a degree in electrical and electronic engineering, computer science, applied mathematics, or mechanical engineering with solid background in applied mathematics and particularly in numerical methods, control theory, and/or optimisation.

The PhD scholarship provides 30K AUD a year tax-free stipend for up-to four years (subject to passing the PhD candidature confirmation after 12 months) as well as tuition fees for the duration of studies. Additionally, up to 15K AUD will be made available for travel funding to visit other research institutes and attending international conferences.

MIDAS is a large and complementary group of academic researchers and postgraduates collaborating across multiple departments within the Melbourne School of Engineering in areas including automation, control, analytics, machine learning, and optimisation.

Expressions of interest are invited from candidates with (or who expect to gain) a first-class honours degree or an equivalent degree in engineering, computer science, physics, mathematics, or a related discipline. Interested candidates should contact Dr. Shames ( directly and include (1) a brief statement of interest in this position with clear indication of preference for the 2 areas mentioned above (maximum 2 pages), (2) their detailed CV, (3) bachelors and masters/honours transcripts, and (4) names and contact details of at least two referees.

Application Closing Date: 1 December 2017.
Start Date: As soon as possible from March 2018.


What questions to ask in a journal club?

I have looked around and thought a bit about what type of questions one (especially students) ask in journal clubs and I came up with the following list. It is not the most complete list and I am happy to hear suggestions about other things to have in mind. Also, it is prepared for students in the areas where engineering and applied mathematics meet, but can be applicable to other areas as well.

  • What is the most important result of the discussed paper?
  • Is the result incremental with well-understood foundations in the area? Is it new to the area but well-understood in another field of engineering/applied maths? Is it world shatteringly new? Or a waste of time?
  • Was the paper clearly written? How was the flow of arguments? Were the  variables defined properly? How was it structured?
  • What is the most interesting aspect of the paper? It does not need to be the same as the most important bit above.
  • What is the most fundamental mathematical concept mentioned and used?
  • What can you say about computational aspects of the paper? For example, how does the proposed method scale? Or how does it perform in real time?
  • How useful is the result? How realistic are the assumptions? How can you relax the assumptions?
  • What would you do differently? How would you improve the paper?