PhD scholarship - Effective AI for multi-stage optimisation of large supply chain operations

PhD scholarship - Effective AI for multi-stage optimisation of large supply chain operations

This scholarship aims to develop practical methods for optimisaton in large supply chain operations. Candidates will work with the world class AI and machine learning experts and real clients' problems.

This scholarship aims to develop practical methods for optimisaton in large supply chain operations. Ideally candidates should have strong AI, machine learning, and optimisation backgrounds. The project team will work with the world class AI and machine learning experts and target at solving real clients' problems. 

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$34,841 per year for 3 years, with a possible 6-month extension

Applications are now open.

31/12/2024

One (1) scholarship available

To be eligible for this scholarship you must: Have a first-class Honours or 2A Honours or equivalent degree in computing technologies; be an Australian citizen, Australian permanent resident or an international student meeting the minimum English language requirements; provide evidence of adequate oral and written communication skills; meet RMIT's entry requirements for the master by research degree (or master coursework including a minor thesis).

Interested candidates should contact Professor Xiaodong Li (xiaodong.li@rmit.edu.au). Please provide a short research proposal outlining your interest and alignment with the proposed research, and why you think you are the best candidate for this project. You should also provide a short CV, your academic transcripts, 2 of your top published research papers (if any).  Successful candidates will be shortlisted and interviewed by Professor Xiaodong Li (RMIT) and Dr Maksud Ibrahimov (Effective AI).

The ideal candidate we are looking for:

  • Passionate about optimisation, experimentation, AI and machine learning, and application of these technologies to business problems;
  • Good coder with at least one of the major programming languages. Python is preferred but not required - candidate can learn on the job;
  • Eager to learn new technologies and try new ideas in a structured way;
  • Willingness to work in the industry in the future as a digital AI practitioner.

This project aims to develop practical methods to address multi-level and multi-stage optimisaton in large supply chain operations. The successful candidate will work closely with the world class experts in AI, machine learning, and optimisation.  The candidate will get exposure to real-world problems. We are experienced coaches and love to help people develop into superstar professionals and digital leaders. By the end of this PhD project, the candidate will be in demand from majority of mining and supply chain companies.

Professor Xiaodong Li (xiaodong.li@rmit.edu.au)

Sustainable Technologies and Systems Platform 

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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

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