Post-Doctoral Research Visit at University of Bordeaux, France

Job Summary

Inria is seeking a highly motivated Post-Doctoral Researcher to join the AT-BOR team at the Inria Center of the University of Bordeaux. The successful candidate will work on a cutting-edge project titled “Inferring structure in complex systems” alongside Dr. Alexandra Jurgens and a dedicated software engineer.

The project focuses on developing mathematical definitions and inference methods for equations of motion on inferred causal structures, bridging the gap between stochastic processes, information theory, and complex dynamical systems.

Post-Doctoral Research Visit at University of Bordeaux, France

Key Job Details

Research Area

• Primary Fields: Stochastic Processes, Information Theory, Nonlinear Dynamics, and Complex Systems.
• Key Focus: Causal state and structure discovery from time series, developing stochastic differential equations for probabilistic state flows, and analyzing the impact of kernel selection on causal structure inference.

Eligibility & Qualifications

• Degree Required: Ph.D. (Thèse) or equivalent in Physics, Mathematics, Computer Science, or a closely related quantitative field.
• Technical Skills:
  • Strong background in stochastic processes, predictive modeling, and information theory.
  • Active interest in complexity, geometry, chaos, and topology.
  • Fluency in scientific coding to help translate mathematical concepts into actionable algorithms (working alongside a software engineer).
• Interdisciplinary Skills: Ability to communicate effectively across diverse fields including computer science, physics, and ecology.
• Language Requirements: Fluency in scientific English (written and spoken); eagerness to publish research in top-tier scientific journals.

Job Description

As a Post-Doctoral Researcher, your primary mission will be to close the inference loop of complex systems by pairing inferred causal states with their governing equations of motion.

Main Activities:

• Mathematical Modeling: Define flows of probabilistic states on inferred attractor structures (generically described by stochastic differential equations).
• Algorithm Development: Collaborate with the team to design implementable algorithms for inferring these equations, identifying special cases where these inferences are solvable.
• Information Theory: Define and develop computational methods/algorithms for information-theoretic measures (e.g., Shannon entropy rate) describing the predictive model.
• Kernel Analysis: Investigate how the choice of kernel affects causal structure inference and related information-theoretic measures.
• Dissemination: Write mathematical reports, draft high-quality scientific articles, and present progress to colleagues, partners, and scientific collaborators.

Benefits & Perks

• Subsidized meals.
• Partial reimbursement of public transportation costs.
• Flexible working hours and teleworking options.
• Full access to state-of-the-art professional and computer equipment.
• Access to vocational training, social security coverage, and community-building social, cultural, and sports activities.

How to Apply

Applications must be submitted online through the official Inria recruitment portal. Please note that applications sent via other channels are not guaranteed to be processed.

Required Application Documents:

1. Curriculum Vitae (CV)
2. Cover Letter
3. Letters of Support (Mandatory)
4. Complete List of Publications

To apply, please visit the official job posting page: Inria Job Portal – Offer 2026-10198.

Defense Security Notice: This position may be assigned to a restricted area (ZRR) to protect national scientific and technical potential. Access authorization is granted by the head of the institution following ministerial approval.

Last Date to Apply: August 31, 2026

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