22 Nov 2025
Job Information
- Organisation/Company
CNRS- Department
Laboratoire d'Informatique de Grenoble- Research Field
Engineering
Computer science
Mathematics- Researcher Profile
First Stage Researcher (R1)- Country
France- Application Deadline
12 Dec 2025 - 23:59 (UTC)- Type of Contract
Temporary- Job Status
Full-time- Hours Per Week
35- Offer Starting Date
1 Feb 2026- Is the job funded through the EU Research Framework Programme?
Not funded by a EU programme- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
The post-doctoral researcher will contribute to the causal abstraction research direction, which aims to build rigorous benchmark for evaluating AI interpretability using the framework of causal abstraction and develop new interpretability methods. Their mission is to advance the theoretical foundations of the project, develop the evaluation metrics, help establish a robust evaluation pipeline for interpretability methods, and build new interpretability algorithms.
The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters. They will collaborate closely with the PI and the PhD students of the team, interact with international partners, and participate in the supervision and coordination of Master's interns involved in the project. Regular preparation of research results, contribution to conference submissions, and participation in project meetings will be part of their activities.
The post-doc will join CNRS in the GetAlp team at the Laboratoire d'Informatique de Grenoble (LIG). GetAlp conducts research in NLP, machine learning, evaluation, and interpretability. The project will be supervised by Maxime Peyrard (CNRS), with collaboration from PhD students and external partners. The researcher will benefit from an active local community in AI and access to GPU computing infrastructure.
Where to apply
- Website
- https://emploi.cnrs.fr/Candidat/Offre/UMR5217-MAXPEY-003/Candidater.aspx
Requirements
- Research Field
- Engineering
- Education Level
- PhD or equivalent
- Research Field
- Computer science
- Education Level
- PhD or equivalent
- Research Field
- Mathematics
- Education Level
- PhD or equivalent
- Languages
- FRENCH
- Level
- Basic
- Research Field
- Engineering
- Years of Research Experience
- None
- Research Field
- Computer science
- Years of Research Experience
- None
- Research Field
- Mathematics
- Years of Research Experience
- None
Additional Information
Eligibility criteria
The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep learning and an interest in interpretability. Excellent programming skills in Python, familiarity with modern neural architectures, and the ability to conduct independent research are expected. Experience in causal modeling, representation learning, or mechanistic interpretability is appreciated. The successful candidate should also demonstrate good scientific communication skills and the ability to collaborate within a research team.
- Website for additional job details
https://emploi.cnrs.fr/Offres/CDD/UMR5217-MAXPEY-003/Default.aspx
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Laboratoire d'Informatique de Grenoble
- Country
- France
- City
- ST MARTIN D HERES
- Geofield
Contact
- City
ST MARTIN D HERES
STATUS: EXPIRED
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