PhD Scholarship in Automated Decision-Making and Recommender Systems
We are seeking a highly motivated PhD student to work on a project funded by the ARC Centre of Excellence for Automated Decision-Making and Society.
Value and duration
$31,885 per annum for three years with a possible extension of six months (full time).
Number of scholarships available
To be eligible for this scholarship you must:
- have a First-Class Honours in Computer Science or equivalent.
- have strong computational, programming, algorithms, and data analysis skills.
- provide evidence of good oral and written communication skills
- demonstrate an ability to work as part of a multi-disciplinary research team
- meet RMIT University’s entry requirements for the Higher Degree by Research programs.
- preferably be an Australian citizen, or Australian permanent resident
How to apply
To apply, please submit the following documents to Jeffrey Chan (firstname.lastname@example.org):
- a cover letter (research statement)
- a copy of electronic academic transcripts
- a CV that includes any publications/awards and the contact details of 2 referees.
- thesis or research reports
For international applicants, evidence of English proficiency may be required.
Once approved, prospective candidates will be required to submit an application for admission to the PhD (Computer Science) program (DR221) as per instructions on this website.
Scholarship applications will only be successful if prospective candidates are provided with an offer for admission.
Applications are open now
Applications will close once a candidate is appointed with intention to start.
Potential projects could encompass one of the following areas and venues that the research could be published in:
Creating a next generation recommender system that enables equitable allocation of constrained resources. Many recommender systems now suggest items or services drawn from resource constrained environments such as tourist destinations. Unlimited use disrupts the limited capacity of such resources: hidden locations become tourist destinations and neighbourhoods become hotel complexes. Recent research has addressed the problem of building recommender systems that are fair to their registered users, but this comes at the profound risk of being unfair to others: so-called third parties. The incorporation and modelling of such third-party views is a critical omission in existing systems. Our next generation recommender system will consider the preferences, tolerances, and social norms of the system's users as well as its third parties and nonusers.
Studying and developing new approaches that combines fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the transportation focus area, can potentially be applicable in other areas. The project is divided into three work packages, roughly one year in length each. For a mid-point review of the project, we would aim to demonstrate results on formulating and testing different fair routing policies in route recommendation.
Terms and conditions
This scholarship will be governed by RMIT's University Research Scholarship Terms and Conditions.
For further information, you can email Jeffrey Chan (email@example.com)