PhD Position: Stopping Rules for Least-Mean Squares via Anytime-Valid Confidence Sequence
Join the SIERRA team at Inria Paris to develop advanced optimization algorithms for machine learning.
Best for:Best for candidates with a strong background in machine learning and a passion for statistical optimization.
Overview
Inria is offering a three-year doctoral position within the SIERRA project team in Paris. The research focuses on developing new optimization algorithms, specifically investigating stopping rules for least-mean squares using anytime-valid confidence sequences. The successful candidate will conduct high-level research in machine learning and statistical methods. Applicants are expected to contribute to the team's ongoing research and innovation efforts in digital sciences.
What you'll do
- Conduct original research in machine learning and statistical optimization.
- Develop and analyze new optimization algorithms.
- Investigate stopping rules for least-mean squares.
- Collaborate with the SIERRA project team on research projects.
- Prepare and publish research findings in academic venues.
- Participate in the scientific life of the Inria research center.
Requirements
Degree required: Master's degree in Machine Learning or equivalent
Degree offered: PhD
Language: English (professional proficiency required for research).
Instruction: English
- Strong academic background in machine learning.
- Proficiency in mathematical optimization.
- Ability to conduct independent research.
- Must hold a Master's degree (Bac + 5) or equivalent.
- Must be eligible to work in France.
- Subject to security clearance for Restricted Regime Zones (ZRR).
Funding & terms
How to apply
Deadline: 2026-10-15
Applications must be submitted exclusively through the official Inria online portal. Candidates should follow the instructions provided on the job posting page to ensure their application is processed.
- CV
- Cover letter
- Academic transcripts
Contact
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