Postdoctoral Research Fellow – Machine Learning

Academic Level A

2 x Fixed Term Position for up to three years

Applications Close Thursday 20th April 2023 at 11.00pm AEST (R-24358)

About This Opportunity

This is an exciting opportunity for two Postdoctoral Research Fellows to contribute to innovative research developments within the scope of effective and robust modeling techniques for analysis and prediction against large-scale social media data, spatio-temporal data, text data, and visual data. The research will explore fundamental theories and advanced deep learning models to create insights from heterogenous data of multimodalities that are generated in various real-world applications. This project will be particularly focused on the collaborative research with social scientists engaged in the Life Course Centre, to investigate the disadvantages in people, places, and opportunities.

The first position will develop advanced computer vision techniques and leverage satellite images to detect land cover and land use changes. Potential downstream applications include disaster evaluation and recovery monitoring, detection of land use by local communities, analysis of accessibility and allocation of public parks.

The second position will develop advanced data-driven machine learning techniques to create insights from variable data sets surrounding people, e.g., social media data, centre link data, financial data, and education profiles, etc. The expected research is mainly on multi-source multimodal data analytics, spanning across information retrieval, correlation detection, causality discovery, recommendation, privacy preserving. Through this project, it is aimed to gain a deeper understanding of the experiences, needs, and challenges faced by individuals and communities.

Both these positions will produce tangible research outcomes, facilitating cross-disciplinary applications and enabling higher efficiency and reliability of solutions for decision making. The outcome of this research is expected to inform the policies and programs to support disadvantaged individuals and families more effectively.

 Key responsibilities include of both roles include but are not limited to: 

1. Research

Investigate, evaluate the developed deep learning techniques in the areas of (i) computer vision, data privacy and satellite imagery (ii) multimodal data analytics (iii) domain adaptation and generalisation

Develop algorithms for the diagnostic, predictive and prescriptive analysis of process data

Develop and test computational algorithms to obtain rich insights from heterogenous data sets

Produce quality research outputs consistent with discipline norms by publishing or exhibiting in high quality outlets.

Participate in applications for competitive research funding to support projects and activities.

Work with colleagues in the development of joint research projects and applications for competitive research funding support.

Contribute to progressing towards transfer of knowledge, technology and practices to research end users through translation, including commercialisation of UQ intellectual property.

Develop a coherent research program and an emerging research profile.

Review and draw upon best practice research methodologies

2. Supervision and Researcher Development

Contribute to the effective supervision of Honours and Higher Degree by Research students (as appropriate).

Participate in events to attract postgraduate students to the research project.

Demonstrates personal effectiveness in supervision and the management of researcher development

3. Citizenship and Service

Proactively be engaged in the Life Course Centre activities.

Represent the research team in industry or funding body forums and develop and maintain a relevant industry network.

Foster the project relations with industry, government departments, professional bodies, and the wider community.

Demonstrate citizenship behaviours that align to the UQ values.

Shows leadership of self through collaboration and active participation in priority activities for the unit

Begin to develop external links and partnerships by cultivating relationships with industry, government departments, professional bodies and the wider community.

Any other duties as reasonably directed by your supervisor.

This position is subject to the . 

About You

Completion or near completion of a PhD in in computer science (preferably in data mining, machine learning, information retrieval, computer vision and multimedia).

Demonstrated track record in computer vision and data management.

Demonstrated expert knowledge and experience in developing deep learning methods for real-world problems associated with images and multimodal data.

Experience in conducting long-term cross-disciplinary or industrial research projects, with tangible outcomes.

Evidence of publication of research findings in top international peer-reviewed journals/conferences relevant to the scope of the project.

Excellent communication and interpersonal skills with the ability to work both independently in a research environment and as part of a cross-disciplinary team and to establish effective relationships with academic and industrial collaborators.

Advanced computer skills in implementing machine learning algorithms, wrangling large-scale datasets, and showcasing research results.

High-level organization and time management skills, with demonstrated capacity to establish and achieve goals.

What We Can Offer

These are both Full-time, 100 % FTE, Fixed-term positions for 3 years at Academic Level A.

The full-time equivalent base salary will be in the range $74,308.68- $99,426.59

plus super of up to 17 %. The total FTE package will be in the range $86,941.16 – $116, 329.11 per annum. 

For further information about UQ’s benefits, please visit and review . 

Questions?

To discuss this role please contact Professor Helen Huang via email at helen . huang @ uq .edu.au

For application queries, please contact stating the job reference number in the subject line. 
 

Want to Apply?

All applicants must supply the following documents: 

Cover letter addressing the About You section

Resume 

 
To satisfy pre-requisite questions and ensure your application can be considered in full, all candidates must apply via the UQ Careers portal by the job closing deadline. Applications received via other channels, including direct email, will not be accepted. 

About The Selection Process

The University of Queensland is committed to ensuring all candidates are provided with the opportunity to attend the panel interviews, however, for those candidates who are unable to attend in person, video interview options will be available.

Other Information

Sponsorship:

Background Checks  

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