Postdoctoral Researcher in Computational Catalysis and Machine Learning

This postdoctoral position at Mohammed VI Polytechnic University (UM6P) focuses on computational catalysis, combining density functional theory (DFT) and machine learning to model heterogeneous catalytic reactions. The successful candidate will build microkinetic models, fine-tune interatomic potentials, and couple reaction kinetics with reactor simulations to predict conversion and selectivity for key reactions like ammonia synthesis and methane reforming. The role emphasizes interdisciplinary collaboration, high-performance computing, and publication of findings in top-tier journals. The position is based in the Materials Science, Energy, and Nano-engineering (MSN) department, which integrates research, innovation, and entrepreneurship to address African and Moroccan challenges.

• Perform plane-wave DFT calculations to determine adsorption energetics, reaction energies, and activation barriers on catalytic surfaces.
• Construct microkinetic models from first-principles energetics and simulate rates, selectivity, and surface coverages under various operating conditions.
• Couple microkinetic models with reactor models to predict conversion and selectivity as functions of operating conditions.
• Assemble DFT training datasets and fine-tune pretrained machine-learned interatomic potentials using in-house DFT calculations.
• Validate machine-learned potentials against withheld DFT data, assessing their reliability across chemical environments and configurations.
• Use validated potentials to accelerate exploration of reaction pathways and adsorbate configurations beyond the reach of direct DFT.
• Compare predicted kinetics and reactor performance with published experimental data.
• Automate and manage reproducible calculation campaigns on HPC resources using Python-based scientific workflows.
• Publish research findings in peer-reviewed journals and present at international conferences.
• Supervise Master’s and PhD students as part of the research team.