Postdoctoral Researcher, AI for Chemical Process Engineering

About the role

Mohammed VI Polytechnic University (UM6P) is recruiting a Postdoctoral Researcher to work on its initiative integrating artificial intelligence into chemical process systems engineering. The project tackles process intensification, sustainability and advanced process control, developing AI-driven frameworks for multi-scale modeling, multi-objective optimization and predictive control of chemical and biochemical processes. It supports smart manufacturing, sustainable energy, green chemistry, the circular economy and CCUS.

Key responsibilities

• Create and implement hybrid AI models combining machine learning with mechanistic frameworks such as physics-informed neural networks and grey-box modeling.
• Build multi-objective optimization frameworks (Pareto optimization) to balance economic, energy efficiency and environmental performance.
• Use reinforcement learning and deep reinforcement learning for autonomous process management and real-time decisions.
• Design and deploy digital twins for virtual commissioning, optimization, fault diagnosis and predictive maintenance.
• Analyze heterogeneous data (historical process data, sensor data, lab results) with unsupervised learning, transfer learning and anomaly detection.
• Collaborate with process engineers and experimentalists to validate models, demonstrate them at pilot scale and transfer technology to industry partners.
• Publish results in peer-reviewed journals, give conference talks and file patents where relevant.
• Oversee graduate students and support capacity building in AI for CPSE at UM6P.

Required profile

• Ph.D. in Chemical Engineering, Process Systems Engineering, Artificial Intelligence, Data Science or a related field.
• Proven experience in steady-state and dynamic process modeling with Aspen Plus, gPROMS or COMSOL Multiphysics.
• Solid understanding of MPC, nonlinear control and optimal control theory.
• Track record of peer-reviewed publications in AI, chemical engineering or process systems engineering.
• Excellent communication skills and ability to work in multidisciplinary, international teams.

Required skills

• Proficiency in Python and MATLAB.
• Experience with TensorFlow, PyTorch and Scikit-learn.
• Data-driven modeling, deep learning and reinforcement learning applied to chemical processes.

Candidates apply by submitting a cover letter, a CV with publications and patents, and contact details for two academic referees, all in a single PDF.