Research Fellow, School of Computing Technologies
- Melbourne, VIC
- Permanent
- Full-time
- Full-time, Fixed Term position until 30 June 2027
- Salary Academic Level B + 17% Superannuation and Flexible Working Arrangements
- Based at the Melbourne CBD campus, and hybrid ways of working
- Interactive information access and retrieval
- Explainable AI
- Responsible automated decision-making systems and evaluation
- Generative AI and Large Language Models
- Completion of a PhD in Computer Science or a relevant discipline area within the past 5 years at the time of appointment, not including periods of career interruption due to carer's responsibilities, parental leave, illness, or disability.
- Strong experience in at least one of the following areas: interactive systems, machine learning, deep learning, or data mining.
- Demonstrated experience in developing and/or using state-of-the-art methods, software and tools in a relevant research context.
- Solid experience in conducting experiments as required in the relevant expertise and subfield, for example:a. Solid experience in the design and conduct of user studies for evaluation of information access systems
- Solid experience in maintaining and contributing to public codebase or repository.
- Solid experience in performing machine learning experiments using multiple large-scale datasets and public benchmarks.
- Solid experience in establishing machine learning and/or deep learning pipeline.
- Scholarly writing skills and experience in preparing publications for a variety of audiences, including relevant publications in high quality Q1 peer reviewed journals and track records in A* conferences as ranked by CORE in AI, machine learning, and data mining, such as ICML, NeurIPS, ICLR, AAAI, KDD, WWW, WSDM, SIGIR, and other relevant A* conferences.
- Strong interest in the technical and societal problems related to the Fairness, Accountability, Transparency and Ethics (FATE) in AI, particularly in problems related to explainability and fairness. An evidence of publication on FATE-related topic is preferable, but not required.
- Ability to work independently to generate distinctive contributions to scholarly knowledge and/or create real world outcomes.
- Demonstrated ability to work effectively and collaboratively as part of a high-achieving and collegial research culture.
- Well-developed oral and interpersonal skills with demonstrated ability to communicate effectively with a wide range of stakeholders and research collaborators, including presentations at seminars, conferences and industry events.
- Optional/preferable: Emerging track record and recognition for high quality research engagement, including development of new research initiatives, competitive research funding, and industry links.
EURAXESS