R&D Intern - Fairness in Deep Learning - Paris
About this role
This master research internship suits students pursuing a degree in applied mathematics, statistics, or machine learning who want to focus on algorithmic fairness in deep learning. Based in the research center of Artefact located in the 9th arrondissement of Paris, France, the position spans four to six months beginning in the winter of 2026-2027.
Role Overview
The research intern will investigate neural networks within a context that aims to guarantee prediction independence regarding continuous sensitive variables such as age, income, or skin color. The selected candidate will work from the Artefact research center in Paris to study how models encode and amplify data biases, focusing on continuous attributes rather than traditional binary or categorical groupings.
Key Responsibilities
Requirements
Skills and Tools
About the Company
Artefact is an international data services company specializing in data transformation consulting. The organization bridges data and business to help clients achieve their commercial objectives through tailored artificial intelligence technologies and agile methodologies. With a team of 2,500 employees, the firm operates across the entire value chain from conception and deployment to training and change management.
How to Apply
Interested candidates should submit their application directly on the official Artefact company careers page.
Skills and tech stack
Questions candidates ask
What is the duration and start date of the internship?
The research internship lasts between 4 to 6 months and begins in the winter of 2026-2027.
Where is the position located?
The role takes place at the research center of Artefact in the 9th arrondissement of Paris, 75009, Paris, France.
What educational background is required?
Candidates must be in a BAC+4 or BAC+5 program studying applied mathematics, statistics, or machine learning at a university or engineering school.
What is the main research focus of the internship?
The intern will study neural networks to ensure prediction independence from continuous sensitive variables like age, income, or skin color, and design new bias reduction methods.
What technical libraries will be used during the project?
The intern will use open-source libraries such as PyTorch and scikit-learn.