Two PhD positions and one postdoc position are available in the School of Computing at The Australian National University (ANU), Canberra, Australia. The research focuses on the intersection of large language models (LLMs), algorithms, and deep learning, aiming to develop next-generation interactive AI agents capable of solving complex real-world computational problems from natural language descriptions. The ARC-funded project investigates equipping LLMs with expert algorithmic and data-centric reasoning, decomposing complex graph problems, and building human-in-the-loop agents that adapt to user feedback and data properties. ANU is Australia’s national university, ranked 32nd in the QS World University Rankings 2026, and has a strong research culture in artificial intelligence and machine learning. The successful candidates will work closely with Prof. Jing Jiang and Dr. Ahad N. Zehmakan in a collaborative and supportive environment. Eligibility: For PhD positions, applicants should have a Bachelor’s degree with Honours or a Master’s degree in Computer Science or a closely related area, a strong academic record, and research publications are advantageous. English language requirements as specified in ANU’s PhD program apply. For the postdoc position, applicants should hold or be close to completing a PhD, with a strong publication record in top AI, ML, DM, or NLP venues. Funding: PhD positions offer a full scholarship and tuition waiver, plus generous professional development, travel, and research equipment support. The postdoc position is at Academic Level B1 (starting at AUD 121,598 per annum, plus superannuation), with additional travel and research equipment support. The project is funded by the Australian Research Council (ARC). Application Process: Interested candidates should email Dr. Ahad N. Zehmakan at [email protected] with the subject 'Prospective PhD/Postdoc Candidate for DP Project', including a complete CV, a link to their Google Scholar profile and/or personal webpage, academic transcripts, a brief statement of fit, and their earliest/ideal start date. Applications are reviewed on a rolling basis until the positions are filled. Keywords: large language models, algorithms, deep learning, artificial intelligence, machine learning, graph problems, data-centric reasoning, human-in-the-loop AI, natural language processing, School of Computing, The Australian National University.