Postdoc: Fairness & Privacy in Trustworthy ML

Inria Villeneuve d'Ascq; Villeneuve-d'Ascq; On-site; EUR 45,000 - 55,000; Full time

Job summary

Inria Villeneuve d'Ascq in Lille, in the MAGNET team, is seeking a post-doctoral researcher to advance fairness and privacy-preserving machine learning. The role focuses on expanding FairGrad, benchmarking it, and integrating with libraries such as AIF360 and Fairlearn, plus building pipelines for learning from locally private data.

The candidate will work under supervision in a collaborative environment, contributing to open research on ethically aware ML and its practical implementations in

Qualifications

• Good command of English.
• Strong background in Python and software development.
• Solid experience in implementation and experimentation.
• Strong mathematical background.
• Solid knowledge of machine learning, statistics and algorithms.
• Some knowledge of fairness and/or privacy is a plus.

Responsibilities

• Review and follow existing libraries on Fair and Privacy preserving ML.
• Maintain, benchmark and expand the FairGrad library.
• Implement, maintain and benchmark a ML pipeline for learning from locally private data.

Skills

English proficiency

Python

Implementation & experimentation

Mathematics

Machine learning

Statistics

Algorithms

Fairness & privacy

Tools

FairGrad

scikit-learn

AIF360

Fairlearn

Job description

Inria Villeneuve d'Ascq in Lille, in the MAGNET team, is seeking a post-doctoral researcher to advance fairness and privacy-preserving machine learning. The role focuses on expanding FairGrad, benchmarking it, and integrating with libraries such as AIF360 and Fairlearn, plus building pipelines for learning from locally private data.

The candidate will work under supervision in a collaborative environment, contributing to open research on ethically aware ML and its practical implementations in