Research Scholarship for Computer Science / Engineering or Math, Swinburne University of Technology, Australia

  • VN:F [1.9.22_1171]
    Rating: 0.0/5 (0 votes cast)

Project title:
Statistical Forecasting of Probabilistic Properties

Research topic:
Quality attributes such as performance, reliability, availability, safety, and security have a probabilistic nature, and are important for almost all software development projects and for projects related to automotive, avionic and medical systems in particular. However it is hard constructing a system that fulfils requirements regarding these quality attributes. Consequently, also quality control at the system runtime is required. Du to the probabilistic nature of these quality attributes this project aims to use statistical monitoring and forecasting techniques (e.g. time series analysis) as a novel quality control instrument for critical system components.

Your Benefits:
Basically, the benefits can be summarized as follows:

  • You will work on real-world research problems. (There will always be opportunities to cooperate with major software and systems engineering companies.)
  • You will be trained in all skills that are required to successfully finish you research project. Our goal is to help you develop the skills, connections, and opportunities required, that ensure a successful postgraduate career.
  • You will create research outputs at the highest standards. In today’s world, it is not only enough to be good, students must be great and competitive compared to other graduate students. Please have a look at our own research outputs.
  • You will get optimal and continuous supervision. My goal is to give you strong support on your research from a technical side. However, we also try to help my students to develop their personal skills. If you like to know more about my supervision style, we can provide contact details of recently graduated students as reference.
  • You study in a friendly and cooperative environment. Australia is known for its friendliness.

We require:
We are interested in a PhD student who has a good academic record (first class honours or equivalent with marks above 85%) with background in one or more of the following areas:

  • time series analysis
  • statistical quality control
  • probabilistic logics and probabilistic verification and probabilistic model checking
  • quality attributes such as performance, reliability, availability, safety, and security
  • software engineering (in the areas of embedded systems, robotics, etc.)
  • software architectures and architecture evaluation
  • formal methods in system design
  • statistics

Since this project involves working with other PhD students andindustrial partner, communication skills and the ability to work in a team environment are especially required.

The scholarship carries a value of more then AUS$20,000+ p.a., with no tuition fees for both Australian and international students. The selection process will be competitive. If you are interested in the research project, please provide the following information via email to lgrunske[at] (please use the following header for you email “PostGradStudies_YourName”):

  • detailed curriculum vitae
  • short statement about you skills related to the area of research
  • an (electronic) copy of undergraduate and postgraduate transcripts (first class honours or equivalent with marks above 85%, A/A+ or a GPA 3.70/4 is required)

For the final application also the following documents are required:

  • filled out application form for post graduated education at the Swinburne University of Technology
  • evidence of English proficiency for non-native English speaker (officially required is an IELTS of 6.5 with no band below 6.0, practically scores above 7.0 are preferred).

Disclaimer: Every effort has been made to ensure the above information is current and correct. However, applicants should contact the appropriate administering body before making an application, as details do change frequently.


You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>