Postdoctoral position in AI: Human-centered Autonomous Discovery Platform for energy materials Mohammed VI Polytechnic University in Morocco

Mohammed VI Polytechnic University (UM6P) is offering a postdoctoral position in AI within the College of Computing (COLCOM) for the ENERGY-A-LAB project. The project aims to develop a human-centered autonomous discovery platform for energy materials, with a focus on battery technologies. The position sits at the intersection of artificial intelligence, scientific machine learning, and energy materials, and is designed for a researcher interested in self-driving laboratories, no-code autonomous workflows, and data-driven discovery.

The successful candidate will join a multidisciplinary research environment at UM6P, an internationally oriented university in Morocco with a strong emphasis on applied research, innovation, and transdisciplinary collaboration. COLCOM highlights computing research across core computer science and allied quantitative fields, and the university emphasizes high-performance computing infrastructure, including its TOUBKAL system.

Research themes mentioned in the advert include computer vision and remote sensing for agriculture, as well as AI knowledge for agriculture through LLM and NLP tools and the creation of open-source datasets. Although the central project focus is energy materials and batteries, the post also invites contributions in adjacent AI and data-centric areas, making it suitable for candidates with broad interests in machine learning, scientific data, and autonomous systems.

This is a research-focused postdoctoral role and does not include teaching duties. Responsibilities include publishing results in reputable journals, presenting at conferences, supervising PhD students, and contributing to research proposal development. The role is intended for someone who can help advance cutting-edge work while supporting doctoral researchers and building new research directions.

Eligibility requires a PhD in Computer Science, Artificial Intelligence, Data Science, or a related discipline such as Computational Physics, Computational Chemistry, or Applied Mathematics. The ideal candidate should have a strong publication record and demonstrated technical strength in machine learning, deep learning, Python-based workflows, active learning, Bayesian optimization, reinforcement learning or decision-making systems, scientific data handling, and optimization under constraints. Experience with knowledge graphs, NLP, information extraction, multi-agent systems, or autonomous systems would be advantageous.

Applications are accepted until the position is filled. Applicants must apply online and also email their materials to [email protected] with the subject line "[Postdoctoral Position Battery]". Required documents include a cover letter, PhD thesis, CV, publication list, and two to three academic references.