Mission

The A. Mathis Group for Computational Neuroscience and AI (CNAI), led by Professor Alexander Mathis, is seeking two postdoctoral fellows to join our team working at the intersection of artificial intelligence and neuroscience. Our research is built around three intertwined questions: how to measure and understand behavior with AI, how brains and embodied agents learn to control the body, and how the brain builds a sense of its body through proprioception. We develop widely-used open-source tools (e.g., DeepLabCut), train biomechanically realistic embodied agents (e.g., MuscleMimic, Kinesis, Arnold), and build AI-based models of sensorimotor processing.

We are recruiting two postdocs:

1. Postdoc in Computer Vision & AI for Behavior Analysis
2. Postdoc in Embodied AI (Reinforcement Learning for Motor Control)

Main duties and responsibilities

For both positions:

• Conduct innovative, independent research aligned with the lab's mission and the candidate's interests
• Contribute to the lab's open-source software, datasets, and benchmarks
• Mentor PhD and Master's students and contribute to the lab's collaborative culture
• Engage with collaborators across EPFL and beyond (neuroscience labs, ecology partners, clinical collaborators)
• Present research at international conferences and workshops

Position 1: Computer Vision & AI for Behavior Analysis

• Contribute to the creation of behavioral datasets for groups of animals
• Develop methods for animal and environment reconstruction
• Develop methods for behavior understanding from multi-view video and audio recordings
• Advance multimodal large language models for fine-grained action understanding and reasoning
• Help shape the next generation of DeepLabCut and related open-source tools used by labs worldwide.

Position 2: Embodied AI

• Train muscle-actuated, biomechanically realistic agents to perform skilled motor tasks using reinforcement learning, imitation learning, and curriculum methods;
• Develop new methods for full-body musculoskeletal control
• Probe links between learned control policies and neural representations of movement in collaboration with experimental labs

Profile

Common requirements:

• PhD (completed or close to completion) in computer science, applied mathematics, computational neuroscience, robotics, physics or a closely related field;
• Strong publication record in relevant venues;
• Solid programming skills in Python and a modern deep-learning framework
• Excellent communication skills in spoken and written English;
• Self-motivated, collaborative, and committed to open science and reproducible research;
• Demonstrated ability to work both independently and as part of a team.

Position 1 — additional desirable expertise:
computer vision, video understanding, action recognition, multimodal/vision-language models, pose estimation, or large-scale self-supervised learning. Familiarity with neuroscience, or ethology is a plus.
Position 2 — additional desirable expertise: 
reinforcement learning, imitation learning, optimal control, dynamical systems, or related ML areas; experience with physics simulators (MuJoCo). Familiarity with motor neuroscience and biomechanics is a plus.

We offer

• A vibrant, collaborative research environment at the intersection of AI and neuroscience
• Access to EPFL's compute infrastructure and to the broader EPFL ecosystem
• Competitive salary in line with EPFL postdoc standards
• Excellent working conditions
• Opportunities for international collaboration, conference travel, and professional development

Informations

• Contract start date: flexible, ideally summer 2026 or as soon as possible thereafter
• Activity rate: 100%
• Contract type: fixed-term, initially one year with the possibility of extension
• Work location: Campus Biotech, Geneva

How to apply

Applications should be submitted exclusively through the EPFL website. Postdoctoral applications should consist of:

• A motivation letter (please indicate which position you are applying for; applications to both positions are welcome)
• A CV with publication list
• Two relevant publications
• The email addresses for two or more referees

For any questions, please reach out by email to [email protected] with the subject line "Postdoc Application 2026 – [Position 1 / Position 2 / Both]". Applications will be processed as they arrive until the positions are filled.

Additional information about our research can be found at https://cnai.epfl.ch.
EPFL is an equal opportunity employer and is committed to fostering a diverse and inclusive workplace.