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Post-Doctoral Research Visit F/M Formal proofs for Machine Learning - Job Opportunity at Inria

Villeneuve d'Ascq, France
Contract
Senior
Posted: August 6, 2025
Hybrid
EUR 45,000-55,000 annually based on French postdoctoral research positions at national institutes, with Inria typically offering competitive packages within the public research sector that include comprehensive benefits and job security

Benefits

Subsidized meal programs providing significant cost savings for daily nutrition
Comprehensive public transport reimbursement reducing commuting expenses
Generous time-off package with 7 weeks annual leave plus 10 RTT days exceeding industry standards
Flexible teleworking arrangements and adaptable working hours supporting work-life balance
Professional-grade equipment provision including videoconferencing and computer loans
Access to social, cultural and sports activities fostering community engagement
Comprehensive vocational training opportunities for continuous professional development
Full social security coverage ensuring complete healthcare protection

Key Responsibilities

Lead the formalization of cutting-edge bandit algorithms in Lean theorem prover, establishing new standards for mathematical rigor in machine learning
Develop sophisticated theoretical frameworks and tools to prove performance guarantees for machine learning algorithms with mathematical certainty
Orchestrate collaborative open-source project management including contribution coordination and code review processes that shape the future of formal methods in AI
Drive research dissemination through high-impact publications and conference presentations, establishing thought leadership in the intersection of formal methods and machine learning

Requirements

Education

PhD or equivalent

Experience

Post-doctoral level

Required Skills

Proficiency with Lean or a similar theorem prover Knowledge of the mathematical tools needed for machine learning theory, in particular probability theory Knowledge of machine learning or bandit algorithms (preferred) Scientific communication skills (speaking, writing) Proficiency in English
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Sauge AI Market Intelligence

Industry Trends

The formal verification field is experiencing unprecedented growth as AI systems become more critical and require mathematical guarantees of correctness, with major tech companies investing billions in formal methods research. The intersection of theorem proving and machine learning represents one of the most promising frontiers in AI safety and reliability, particularly as regulatory frameworks increasingly demand provable guarantees for AI systems in high-stakes applications. Lean theorem prover has emerged as the dominant platform for modern formal mathematics, with substantial backing from Microsoft Research and growing adoption in both academic and industrial settings. The recent success of AI-assisted theorem proving, exemplified by systems like GPT-f and Lean's integration with large language models, has created a surge in demand for researchers who can bridge formal methods and machine learning. The bandit algorithm research area has seen explosive growth due to applications in recommendation systems, clinical trials, and autonomous systems, with companies like Netflix, Amazon, and pharmaceutical giants heavily investing in this technology. The need for formal guarantees in these applications has created a unique niche for researchers who can provide mathematical proofs of algorithm performance.

Role Significance

Likely leading a small specialized team of 2-4 researchers within the broader SCOOL team, with potential for expanding the team as the project gains momentum and attracts external contributors from the international formal methods and machine learning communities
This represents a senior research position requiring independent leadership capabilities and the ability to drive innovative research at the intersection of two highly specialized fields. The role demands not only technical expertise but also the vision to establish new research directions and build academic communities around emerging methodologies.

Key Projects

Development of the first comprehensive formal library for bandit algorithms with complete mathematical proofs Creation of simulation environments that can be formally verified within the Lean ecosystem Establishment of benchmarking frameworks for comparing formally verified machine learning algorithms Integration of AI-assisted proof generation with formal verification workflows

Success Factors

Deep mastery of both Lean theorem proving and probability theory is absolutely critical, as the role requires translating complex mathematical concepts between informal machine learning literature and formal mathematical frameworks. The ability to work at this intersection will determine the project's success and impact. Exceptional project management and community building skills are essential, as the role involves coordinating contributions from diverse research communities and maintaining code quality standards that will influence the field's development for years to come. Strong research intuition to identify which aspects of machine learning theory are most amenable to formalization and will provide the greatest impact for the broader research community, balancing theoretical rigor with practical applicability.

Market Demand

Very high demand with extremely limited supply of qualified candidates who possess both Lean expertise and machine learning theory knowledge, making this one of the most sought-after skill combinations in academic and industrial research

Important Skills

Critical Skills

Lean theorem proving expertise is absolutely essential as it forms the foundation of all project deliverables. Without deep proficiency in Lean, including understanding of its type system, tactic language, and mathematical library structure, it would be impossible to make meaningful progress on formalizing machine learning algorithms. This skill is rare and highly valued, with fewer than a few hundred experts worldwide. Advanced probability theory knowledge is crucial for translating informal machine learning guarantees into formal mathematical statements that can be proven within Lean's framework. This requires not just computational proficiency but deep understanding of measure theory, concentration inequalities, and stochastic processes that underpin modern machine learning theory.

Beneficial Skills

Experience with collaborative software development and open-source project management would significantly enhance the candidate's ability to build and maintain the research community around the project. As the field grows, these skills become increasingly important for maximizing research impact. Background in programming language theory and type systems would provide valuable insights for designing elegant formalization strategies and could lead to methodological contributions that extend beyond the immediate project scope.

Unique Aspects

This position represents a rare opportunity to pioneer an entirely new research area at the intersection of formal methods and machine learning, with the potential to establish foundational frameworks that will influence both fields for decades. The combination of Lean expertise requirements with machine learning theory makes this one of the most specialized and forward-looking research positions currently available.
The role offers exceptional visibility within both the formal methods and machine learning communities, with opportunities to shape the direction of two rapidly evolving fields simultaneously. The open-source nature of the work ensures maximum impact and recognition within the global research community.
Working within Inria's exploratory action framework provides unusual research freedom combined with institutional support, allowing for high-risk, high-reward research that might not be feasible in more commercially-oriented environments.

Career Growth

Progression to senior industry or academic positions typically occurs within 2-3 years post completion, given the extremely high demand and limited supply of expertise in this area

Potential Next Roles

Senior Research Scientist positions at major technology companies focusing on AI safety and formal verification Academic faculty positions specializing in formal methods, theorem proving, or theoretical machine learning at top-tier universities Principal Researcher roles at research institutes like Microsoft Research, Google DeepMind, or similar organizations working on AI alignment and safety

Company Overview

Inria

Inria stands as France's premier national research institute for digital sciences, employing over 2,600 people across 215 agile research teams. As the country's equivalent to institutions like MIT's Computer Science and Artificial Intelligence Laboratory, Inria has established itself as a global leader in computational research with a particular strength in theoretical computer science and its practical applications.

Inria maintains a dominant position in European research computing, consistently ranking among the top research institutes globally for computer science publications and innovation. The institute's strong ties with both academic institutions and industry partners provide unparalleled access to cutting-edge research opportunities and real-world application scenarios.
The Lille center represents a strategic hub in Northern France's growing tech ecosystem, positioned at the heart of EuraTechnologies, one of Europe's largest startup incubators. This location provides unique opportunities for technology transfer and collaboration with both established companies and emerging startups in the region.
Inria fosters a collaborative, intellectually rigorous environment that balances academic freedom with practical impact objectives. The institute's culture emphasizes open science, international collaboration, and the translation of theoretical advances into societal benefits, creating an ideal environment for groundbreaking interdisciplinary research.
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