On-demand Dataset Builder

About the Project

This project will develop a prototype system to showcase the scalability, reliability, and usability of an AI-assisted dataset builder for effective and efficient discovery and curation of multi-source and multi-modal educational data. Working in close collaboration with domain experts and end users from the Queensland Department of Education, the project team will review and investigate best practices for constructing on-demand data sets and the concept of “data as a service”. The project will also develop new methods for AI-assisted on-demand dataset builder and will evaluate with a human-centred lens. The research will result in validated methods and a prototype implementation of the system, road-tested with end users. 

Queensland Department of Education are empowering confident and creative lifelong learners through a student-centred approach to learning and wellbeing. This partnership with CIRES will support the department in developing a robust data infrastructure pipeline, which can be applied to demonstrator projects to enhance internal data capability and help address policy questions.  



About the Candidate

The ARC Training Centre for Information Resilience (CIRES) invites highly motivated and committed candidates to apply for this fully-funded PhD position. The successful candidate will work in close collaboration with their advisory team, and leading experts in the Queensland Department of Education, and complete the equivalent of a 12 month placement during their PhD with the Department. 

This project aims to develop an on-demand dataset builder to facilitate effective and efficient discovery and curation of multi-source and multi-modal educational data. For this position, CIRES is seeking a candidate with a good background in data science, data analytics, or machine learning; and proficiency in python programming language and machine learning software packages such as Pytorch. Track record of publishing highquality conference or journal paper and experience working with and ingesting structured and unstructured date from multiple sources are desirable. 

Applications for this PhD position are open and close on the 16th May 2023.

Apply Now!


project researchers
Dr Hassan Khosravi (Principal Advisor)
Prof Shazia Sadiq
A/Prof Wojtek Tomaszewski
Dr Angela Ferguson (Qld Dept. of Education)
partner investigator
Queensland Department of Education