Entreprise :

Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Moroccos frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.

Poste :

We are seeking a talented and motivated Research Assistant (Data Scientist) to join our team. The project focuses on combining experimental data with machine learning, process simulation, and techno-economic/environmental analysis (TEA/LCA) to optimize biomass valorisation for sustainable materials.

The candidate will work at the intersection of materials science and data science, contributing to building predictive models, optimizing process parameters, and supporting the integration of AI-driven approaches for sustainable material production.

Key Responsibilities:

Develop and implement machine learning and AI models for predicting and optimizing catalytic graphitization outcomes (yield, crystallinity, ID/IG ratio, etc.).
Integrate data with Aspen Plus simulations for process modeling and scale-up scenarios.
Conduct data preprocessing, statistical analysis, and visualization for materials characterization datasets.
Support the development of TEA/LCA frameworks to evaluate economic and environmental performance.
Collaborate with interdisciplinary researchers in materials chemistry, AI, and process engineering.
Contribute to scientific publications, reports, and presentations.

Profil recherché :

Bac+5 with equivalent research experience in Computer Science, Data Science, Artificial Intelligence, or a related field.
Strong expertise in machine learning, deep learning, and data-driven modeling (PyTorch, etc.).
Experience with data analysis and visualization tools (Python, Pandas, NumPy, Matplotlib, Seaborn).
Familiarity with big data tools (Hadoop, Spark, Kafka) is a plus.
Interest in sustainability, biomass valorization, and materials science applications.
Good publication record and good communication skills.

Research Assistant (Data Scientist in ML & Process Optimization for Biomass Valorization)