Alexander Mathis

EPFL is recruiting two postdoctoral fellows for research at the intersection of artificial intelligence and neuroscience . The positions are in the group of Alexander Mathis at the École polytechnique fédérale de Lausanne (EPFL), Switzerland. The lab works on understanding 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. Open postdoc areas: 1) Postdoc in Computer Vision & AI for Behavior Analysis 2) Postdoc in Embodied AI (Reinforcement Learning for Motor Control) The research environment includes widely used open-source tools such as DeepLabCut and projects involving biomechanically realistic embodied agents such as MuscleMimic , Kinesis , and Arnold . The work is strongly oriented toward computational neuroscience , sensorimotor processing , behavior analysis , computer vision , and reinforcement learning . Eligibility highlights: this is a postdoctoral recruitment, so applicants should have a strong background and research experience aligned with AI, neuroscience, embodied AI, motor control, or related quantitative fields. Funding: the post announces postdoctoral positions at EPFL, but no stipend or salary amount is stated in the excerpt. How to apply: read the EPFL careers posting for the full job description and application instructions. Use the job link to access the application portal and submit your materials through EPFL's recruitment system. Application window: no deadline is stated in the provided text.

EPFL’s A. Mathis Group for Computational Neuroscience and AI (CNAI) is recruiting two postdoctoral fellows for research at the intersection of artificial intelligence and neuroscience . Position 1: Computer Vision & AI for Behavior Analysis focuses on behavioral datasets, animal and environment reconstruction, multi-view video and audio understanding, multimodal large language models, and the next generation of DeepLabCut and related open-source tools. Position 2: Embodied AI focuses on muscle-actuated, biomechanically realistic agents, reinforcement learning, imitation learning, curriculum methods, full-body musculoskeletal control, and links between learned control policies and neural representations of movement. Applicants should have a PhD completed or near completion in computer science, applied mathematics, computational neuroscience, robotics, physics, or a closely related field, plus a strong publication record, strong Python/deep-learning skills, excellent English, and a collaborative, open-science mindset. Helpful background includes computer vision, video understanding, action recognition, vision-language models, pose estimation, self-supervised learning, reinforcement learning, optimal control, dynamical systems, MuJoCo, motor neuroscience, and biomechanics. The role is based at Campus Biotech, Geneva, Switzerland . EPFL offers a vibrant interdisciplinary environment, access to compute infrastructure, competitive postdoc salary, and opportunities for international collaboration and conference travel. The contract starts flexibly, ideally in summer 2026 or soon after, at 100% activity rate, initially for one year with possible extension. Apply through the EPFL careers portal with a motivation letter indicating the position(s), CV with publication list, two relevant publications, and referee email addresses. Questions can be sent to [email protected] .