Post-Doc in Machine Learning for Fair Recommending Systems
Télécom Paris is recruiting a postdoctoral researcher in Machine Learning for a project on fairness issues in recommendation engines.
The Research group S2A at Télécom Paris is recruiting a postdoctoral researcher in Machine Learning to work on fairness issues for recommendation engines. The project involves an interdisciplinary collaboration with the SES department and the Caisse des Dépôts et Consignations.
Research activities will focus on fairness issues for recommendation engines designed by means of machine-learning methods. The post-doc’s mission will include applied work on a deployed recommendation system, aimed at quantifying the presence of different types of bias.
- Public service recommender system
- Fair and explainable AI
- Bias mitigation
- Multi-sided fairness
Applicants should submit a single PDF file that includes a motivation letter, curriculum vitae, one or two major publications, and contact information for one or two references.
Important dates: First-Quarter 2025 (interviews) and Spring 2025 (beginning). Contact Stephan Clémencon, Charlotte Laclau, or Winston Maxwell for information/application.
Tags: postdoc, machine learning, fairness, recommender system, public service, fair and explainable AI, bias mitigation, multi-sided fairness