The UTS Advanced Analytics Institute is recruiting for a Postdoctoral Research Fellow in Automated Machine Learning to play a key role in building on research concerned with the automation of predictive systems building, deployment and maintenance. The position will be based in our 14-level smart building with world-class facilities and astonishing light-filled architecture. It is centrally located in the heart of Sydney. This position will report to Professor Bogdan Gabrys, Director of AAi.
About the centre
The Advanced Analytics Institute (AAi) is a world-leading research centre with a focus on big data, data sciences and data analytics. The Postdoctoral Research Fellow will conduct research in the area of complex learning/adaptive systems with a focus on multi-component, multi-level, multi-objective optimisation and mechanisms in the context of learning systems.
AAi research delivers real-world solutions to contemporary big data questions and assists industry partners to use data as a tool for effective business decisions. AAi researchers are internationally recognised for their expertise and projects across automated machine learning, data mining, advanced/predictive analytics, diagnostic analysis, decision support systems, time series analysis, network science, bioinformatics and multimedia analytics. The extensive research networks coupled with Their focus on practice-based innovation has lead AAi to be preferred partner for both industry and government.
About the Postdoctoral in Machine Learning
The key responsibilities will include:
- Collaboration with industry partners on data science and advanced analytics projects;
- Working towards developing state-of-the-art methods for automated machine learning;
- Establishing and developing productive collaborative research activity across the institute, Faculty and wider UTS community and externally with other broader-based research partners;
- Producing research publications and supporting applications for internal and external research grants with the aim of developing a funded program of research in automated machine learning;
- Supervising research students and contributing to their development as future researchers.
Eligibility
The main experience and skills required include:
- A strong research profile as evidenced by peer-reviewed journal and conference publications.
- Proven ability to undertake empirical research.
- Demonstrated ability to forge links with the Data Science and Machine Learning profession and other key stakeholders.
- Demonstrated knowledge in any of the following areas: (Automated) Machine Learning, Computational Intelligence, Complex Adaptive Systems, Pervasively Adaptive Software Systems or Predictive Modeling.
- A doctorate in computer science, mathematics, physics, engineering, statistics or a similar discipline.
- Strong programming skills using any or a combination of Java, C++, C#, Python, R, and/or Matlab.
Remuneration & Benefits
Base Salary Range: $103,981 to $123,067 pa (Level 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, childcare centres, generous parental leave and salary packaging opportunities.
This position is full-time and an appointment will be made on a fixed-term basis for 2 years.
Their vision is to be a leading public university of technology recognised for global impact. UTS is 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.
How To Apply
For the full list of the selection criteria and role responsibilities please follow this link and download the Position Statement from the UTS website.
UTS is committed to diversity and inclusion in their workforce and UTS encourage applicants were 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 – Click here.
As you will be unable to save your application once started, please have all the required documents and information available prior to commencing.
Please ensure that the file name for each document submitted includes IRC148268.
Specific enquiries or issues with your application may be directed to the UTS Recruitment Team at [email protected] or on +61 (0) 2 9514 1080.
Please be advised that as part of the selection process you may be requested to deliver a presentation, the audience for which may include individuals, not on the Selection Panel.
Important Dates
Closing Date: Wednesday 20th November 2019 at 11.59pm (AEST)
