Research Intern: Bayesian ML & Federated Learning

Sigma Nova; Paris; On-site; EUR 8,900 - 13,000; Full time

Job summary

Sigma Nova invites a research intern to work in Paris from March to April 2027, exploring fundamental ML questions about adapting to new datasets, reliable uncertainty, and privacy-aware learning. You’ll join researchers to connect foundation models with probability, Bayesian inference, and optimal transport, shaping a topic with potential for publication.

The role blends mathematical thinking with hands-on experiments, offering mentorship, access to GPU resources, and room to influence the

Qualifications

• Master’s-level training in applied mathematics, statistics, ML, or related field.
• Strong Python skills and PyTorch experience.
• Solid foundations in probability, linear algebra, and optimization.
• Ability to read research papers and design reproducible experiments.
• Interest in Bayesian inference, optimal transport, or privacy-preserving learning.

Responsibilities

• Investigate how models adapt to new datasets.
• Explore how models provide uncertainty estimates with predictions.
• Study learning from multiple data sources while preserving privacy.
• Contribute to experiments and potential publications.
• Collaborate with researchers on probabilistic and transport-based methods.

Skills

Python

PyTorch

Probability

Linear algebra

Optimization

Reading papers

Reproducible experiments

Privacy-preserving learning

Education

Master's degree in applied mathematics, statistics, ML, or related field

Job description

Sigma Nova invites a research intern to work in Paris from March to April 2027, exploring fundamental ML questions about adapting to new datasets, reliable uncertainty, and privacy-aware learning. You’ll join researchers to connect foundation models with probability, Bayesian inference, and optimal transport, shaping a topic with potential for publication.

The role blends mathematical thinking with hands-on experiments, offering mentorship, access to GPU resources, and room to influence the