Faculty of Engineering & IT, School of Computer Science

At UTS, the concepts of equity and social justice are key to our core and purpose – we are recognised widely as supporting inclusivity and valuing diversity. Cited as a WGEA Employer of Choice since the inception of the award, we are now among the first Australian institutions to receive the Athena SWAN Bronze Accreditation for our commitment to action addressing gender equity in the STEMM disciplines. UTS Equal Futures celebrates and supports women in academia through every stage of their career.

As part of Athena SWAN, UTS has set an overarching target of 40 per cent academic women in STEMM by 2022. The School of Computer Science is committed to UTS’s target and supporting the career development of women academics.   

The School of Computer Science in the Faculty of Engineering & IT has an opening for a Postdoctoral Research Fellow position to conduct research in machine learning and data analytics. This is a great opportunity to work with an award-winning team. Your career development will benefit from interactions with UTS’s world-class researchers. The selected candidate will be expected to perform innovative and impactful research on data analytics related to infrastructure and asset management.

About the role

The position reports to the Director of a Data Science Institute in FEIT. The director role is currently held by Executive Director Data Science, Distinguished Professor Fang Chen. Research and industry engagement is to be recognised as world-leading and for it to be recognised by Australian industry and government agencies as a leading source of knowledge and expertise. Research will include design and develop innovative technology to provide comprehensive solutions to real-world asset and infrastructure problems.

• Undertake innovative and impactful research on machine learning and data analytics through academic and industry projects.
• Research on data analytics and related topics for infrastructure and asset management.
• Develop algorithm, interface, and system for intelligent infrastructure/asset management.
• Conduct data pre-processing, analysis, and other necessary tasks related to the research problem.
• Apply for internal and external research grants with the aim of developing a funded program of research.

About you:

• Research record evidenced by high quality publications on top-tier conferences and journals in the areas of machine learning, data mining and data analytics.
• Demonstrated knowledge in areas relevant to machine learning, data mining and data analytics.
• Desirable to have knowledge in Bayesian nonparametrics, nonhomogeneous stochastic processes, large-scale data mining and cloud computing.
• Completion of a PhD degree in machine learning, data mining, or related areas.
• Experience with dynamic processes/networks, or spatial-temporal data analytics, and experience with software tool development based on popular platforms such as Spark, Azure, etc.

Base Salary Range: $78,170to $123,067 pa (Level A - B)

This role attracts 17% superannuation (pension) in addition to the base salary.

UTS staff also benefit from a wide range of Employee Benefits include flexible work practices, child care centres, generous parental leave and salary packaging opportunities.

This position is full-time and appointment will be made on a fixed term basis for 54 months.

Our vision is to be a leading public university of technology recognised for our global impact. We are a dynamic and innovative university, ranked by the Times Higher Education as Australia’s top young university, and located centrally in one of the world’s most liveable cities. With a culturally diverse campus life and extensive international exchange and research programs, UTS prepares graduates for the workplaces of today and tomorrow. 

For the full list of the selection criteria and role responsibilities please click the apply link and download the Position Statement from the UTS website.

UTS is committed to diversity and inclusion in our workforce and we encourage applicants where relevant to include a relative to opportunity or career disruption/break statement within their CV.

You are required to address the selection criteria in your submission in a separate document. For information to assist you with compiling statements to answer the selection criteria, please visit Answering Selection Criteria​

Only those applications submitted via the UTS online recruitment system will be accepted.  Current UTS employees should apply through their UTS Employee Self Service function. If you are an internal applicant and need help with how to apply through NEO 

As you will be unable to save your application once started, please have all required documents and information available prior to commencing.

Please ensure that the file name for each document submitted includes IRC133740.

Specific enquiries or issues with your application may be directed to the UTS Recruitment Team at recruitment@uts.edu.au or on +61 (0) 2 9514 1080.

Please be advised that as part of the selection process that you may be requested to deliver a presentation, the audience for which may include individuals not on the Selection Panel.

Closing Date:  Thursday 27^th June 2019 at 11.59pm (AEST)

Please note: If you have a disability that requires adjustment to the recruitment process or an alternative application pathway please contact recruitment@uts.edu.au for assistance.

At UTS, the concepts of equity and social justice are key to our core and purpose – we are recognised widely as supporting inclusivity and valuing diversity through our Wingara Indigenous Employment Strategy, Social Impact Framework and UTS Access and Inclusion Plan.

Cited as a WGEA Employer of Choice since the inception of the award, we are now among the first Australian institutions to receive the Athena SWAN Bronze Accreditation for our commitment to action addressing gender equity in the STEMM disciplines.

We welcome applications from women, Indigenous Australians, people with disability, those who identify as LGBTIQ and applicants from culturally and linguistically diverse backgrounds.