Mounir Ghogho
3 months ago
COLCOM - Postdoctoral Researcher in Embodied AI for Edge Robotics Mohammed VI Polytechnic University in
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
Mohammed VI Polytechnic University
University
Mohammed VI Polytechnic University

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About this position
The College of Computing at Mohammed VI Polytechnic University (UM6P) in Morocco is seeking a postdoctoral researcher for the COLCOM project, focusing on Embodied AI for Edge Robotics. UM6P is a leading, internationally oriented institution committed to high standards in teaching and research, with a strong emphasis on sustainable economic development for Morocco and Africa. The university fosters applied research, innovation, and transdisciplinary collaboration, providing a dynamic environment for experimentation and academic growth.
The successful candidate will join a vibrant research community and work under the mentorship of Professor Mounir Ghogho. The research will center on developing and validating novel robot learning methods for control and decision-making on edge robotic platforms. Key areas include reinforcement learning, imitation learning, and the integration of large language, vision–language, and vision–language–action models to enhance generalization and efficiency. The position aims to design lightweight learning architectures suitable for resource-constrained robotic systems, with access to state-of-the-art computational resources.
Responsibilities include developing new methods tailored to edge robotics, testing these approaches in both simulated and real environments, and publishing findings in top-tier machine learning and robotics venues. The postdoc will be part of a research-education program that covers all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems, and security.
Applicants must have a Ph.D. in Computer Science, Machine Learning, Robotics, or a related discipline, with a strong background in reinforcement and imitation learning for robotics. Experience with large language models (LLM), vision-language models (VLM), or vision-language-action models (VLA) is required, as well as proficiency in PyTorch and common ML libraries. Familiarity with ROS and simulators such as Isaac Gym or MuJoCo is a plus. Candidates should demonstrate multidisciplinary research ability, contribute to funded research programs, and possess strong English communication skills.
To apply, candidates should prepare a detailed CV, cover letter summarizing their background, research works, projects, publications, and key achievements, as well as research and teaching plans, entrepreneurial ideas, and services to the UM6P community. Contact information for three referees is also required. Applications can be submitted via the provided link. The position offers an opportunity to contribute to cutting-edge research in robotics and AI within a supportive and innovative academic environment.
Funding details
Available
What's required
Applicants must hold a Ph.D. in Computer Science, Machine Learning, Robotics, or a closely related field. A strong background in reinforcement and imitation learning for robotics is required. Experience with large language models (LLM), vision-language models (VLM), or vision-language-action models (VLA) is expected. Proficiency in machine learning frameworks such as PyTorch and common ML libraries is necessary. Experience with ROS and simulators such as Isaac Gym or MuJoCo is considered a plus. Candidates should demonstrate the ability to perform multidisciplinary research and contribute to funded research programs. Good English communication skills, both verbal and written, are important.
How to apply
Prepare a detailed CV, cover letter with a summary of your background, research works, projects, publications, and key achievements. Include research and teaching plans, entrepreneurial ideas, and services to the UM6P community. Provide contact information for three referees. Apply via the provided application link.
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