Rosa Taghikhah
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PhD Opportunity in Explainable/Responsible AI and Operations Research/Reinforcement Learning at the University of Sydney University of Sydney in Australia
Degree Level
PhD
Field of study
Computer Science
Funding
Full tuition fee waiver plus a tax-free living stipend of AUD 42,754 to AUD 44,293 per year.
Deadline
Sep 11, 2026
Country
Australia
University
University of Sydney

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About this position
Rosa Taghikhah, Senior Lecturer at the University of Sydney, is accepting applications for PhD candidates to join her research group.
The project sits at the intersection of Explainable AI, Responsible AI, Operations Research, and Reinforcement Learning, with a focus on helping stakeholders make better decisions. This is a strong fit for students interested in business analytics, decision support, optimization, and machine learning for real-world impact.
Funding: The position includes a full tuition fee waiver and a tax-free living stipend of $42,754–$44,293 per year.
Eligibility: Open to outstanding domestic and international applicants. A strong research background is requested, and applicants should align their research interests with the advertised themes.
Deadline: Rounds 1 & 2 for early 2027 entry close on September 11, 2026.
How to apply: Review the official University of Sydney postgraduate research portal, then email Rosa Taghikhah with your CV, academic transcripts, and a brief summary of your research ideas before the deadline.
Funding details
Full tuition fee waiver plus a tax-free living stipend of AUD 42,754 to AUD 44,293 per year.
What's required
Applicants should be ambitious PhD candidates with a strong research background. The opportunity is open to outstanding domestic and international applicants. Research interests should align with Explainable/Responsible AI and Operations Research/Reinforcement Learning.
How to apply
Review the University of Sydney research portal details, then email Rosa Taghikhah directly with your CV, academic transcripts, and a brief summary of your research ideas before the deadline.
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