Job DescriptionGriffith's Institute for Integrated and Intelligent Systems (IIIS) specialises in artificial intelligence, computer image processing. Our ongoing quest to incorporate human behaviours into intelligence devices has secured consistent global recognition and cemented its place as an international leader in the field. Innovative, exploratory and entrepreneurial, the IIIS develops technologies with real-life applications.As a Research Fellow, you'll take on complex local and global challenges, using your skills and experience to advance 'Temporal Graph Mining for Anomaly Detection on Dynamic Streaming Networks' and drive meaningful change. Here's how you'll make it matter:You will work with world-class researchers in the fields of data mining and machine learning, fostering an environment of innovation and discovery.You will conduct and lead groundbreaking research in graph machine learning with practical applications that address real-world problems.You will establish a distinguished track record by pushing the frontiers of research and contributing high-quality papers to prestigious AI conferences and journals.You will work with the Chief Investigator (CI) and gain valuable experience in supervising higher degree research (HDR) candidates.This is a fixed term 3 year, full time position and will be primarily based at the Griffith University Gold Coast campus. As Griffith is a multi-campus University you may be required to work across other campus locations.Griffith University's campuses are located on the lands of the Yugarabul, Yuggera, Jagera, Turrbal, Yugambeh and Kombumerri peoples.Salary RangeThe full time equivalent base salary will be Research Fellow, Grade 1 range $84, - $99, per annum + 17% superannuation. The total FTE package will be in the range $99, - $, per annum.QualificationsWhat matters most is your drive to create a brighter future that benefits all. Through our core principles of excellence, ethics and engagement, you'll thrive on seeing the direct and lasting impact you'll have on every community and every future.You will also have:A solid research foundation in graph machine learning and/or anomaly detection, demonstrating your expertise in these cutting-edge areas.A robust publication record, with work featured in leading AI conferences and journals including KDD, NeurIPS, WWW, WSDM, AAAI, TKDE, and TNNLS.Proven ability to work effectively both as part of a team and autonomously, showcasing flexibility and self-motivation.Experience in mentoring and guiding research students or assistants, highlighting your leadership skills and commitment to academic growth.
