Enhancing Efficiency of Foundational Models

Fully funded PhD scholarships are available at the Data Science group, University of Queensland for the following project (for start in Oct 2025/Jan 2026). 

This project aims to improve efficiency in deep learning models. This project will be part the Data Science Research Group, Information Technology and Electrical Engineering School, at the University of Queensland located in Brisbane, Australia.

The Data Science group researches and develops innovative and practical solutions for business, scientific and social applications in the realm of big data. The group encompasses a variety of research strengths, including: Data and knowledge engineering, Information Retrieval, Computer Vision, and Complex and Intelligent Systems. You will join a world-leading research group currently composed of 13 academic staff members (including 6 full professors, two DECRA fellows and 2 Future Fellows), 7 research fellows and over 40 PhD students. Members of the group have a successful track record of publishing in top conferences and journals such as ACM SIGIR, ACM CIKM, The Web Conference (WWW), SIGMOD, CVPR, ICCV, ICML, PAMI, JMLR, ICLR and various ACM and IEEE transactions.

The research environment available to the project is world-class. The University of Queensland (UQ) has a strong and internationally focused research culture. It is ranked in the top 1% of world universities in three widely publicised international University rankings.

This project is supported by the Research project scholarship.

Learn more about the Research project scholarship.

Your application will be assessed on a competitive basis.

We take into account your:

• previous academic record
• publication record
• honours and awards
• employment history

A working knowledge of programming and algorithmic skills, knowledge of machine learning techniques, particularly deep learning, would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of machine learning and computer vision and the potential for scholastic success.

A background or knowledge of linear algebra and multimodal learning is highly desirable.

To be considered for this scholarship, please email the following documents to Dr Mahsa Baktashmotlagh (m.baktashmotlagh@uq.edu.au):

• Cover letter
• CV
• Academic transcript/s
• Evidence for meeting UQ's English language proficiency requirements eg TOEFL, IELTS

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the UQ Study website.