Postdoctoral Research Fellow in Software Data Mining at Swinburne University of Technology

Postdoctoral Research Fellow in Software Data Mining-AT-Swinburne University of Technology (Melbourne, Australia)
? Academic Level A: $78,904 - $84,656 plus 17% superannuation
? Full-time, fixed-term for two years based at the Hawthorn campus
A postdoctoral research fellow is required to join a research team investigating the automated creation of virtual deployment environments for enterprise software systems. This is part of an Australian Research Council Linkage Project, involving Swinburne University of Technology, the University of Melbourne and CA Technologies (NASDAQ: CA).
Today's software industry demands a short development cycle and continuous delivery for software systems and services, as highlighted by the DevOps movement. To meet such industry needs, automated system testing needs to be conducted against production-like conditions throughout the development cycle. The highly interconnected nature of enterprise software systems poses a particular challenge, as the behaviour of any software service depends on the specific interconnections with other services in the production environment. To this end, this project aims to develop techniques that automatically extract/mine executable behaviour models (i.e., light-weight, realistic emulations) of dependency software services from their runtime interaction traces, to form part of an emulated production-like environment for system testing.
Skills and Experience
To be successful in this role you will need to demonstrate the following:
? An earned PhD or PhD thesis under examination in software engineering, computer science or a related area.
? Significant research experience and ability in the key areas relevant to the research project, namely, data mining, software data analysis and/or machine learning.
? Track record for high-quality research as evidenced by publications in top journals and conferences. This must be in the areas of data mining, software data analysis and/or machine learning.
? Ability to supervise PhD students.
? Experience and strong ability in software development.
A full list of the selection criteria is available in the position description for this position on the Swinburne jobs site https://swinjobs.nga.net.au/
How to apply
To start an application, go to the above job site, follow the link for the specific position (position number: 32121) and submit a resume, cover letter and response to the Key Selection Criteria, as listed in the Position Description.
Please do not email or send paper applications, all applications must be submitted online.
For further information, please contact Professor Jun Han on +61 3 9241 5732 or jhan-AT-swin.edu.au.
If you are experiencing technical difficulties submitting your application, please contact the Recruitment team on +61 3 9214 8600 (option 2).
Refer to position number: 32121
Applications close: 5pm on 3 September 2016 (AEST)