Research Scientist in Data Science & Machine Learning - Rabat
Secteur de l’entreprise : Enseignement / Formation
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.
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Culture de l'entreprise :
UM6P – Université Mohammed VI Polytechnique se caractérise par une culture fortement orientée innovation, où la créativité, l’expérimentation et l’audace intellectuelle constituent des piliers essentiels. L’université encourage l’initiative, l’ouverture d’esprit et l’autonomie, dans un environnement stimulant tourné vers la recherche, l’entrepreneuriat et l’impact. Cette dynamique innovante est enrichie par une dimension coopérative solide, valorisant la collaboration, le partage des savoirs et le développement humain. Une orientation vers la performance et l’excellence complète l’ensemble, tandis que les processus formels restent volontairement plus légers pour préserver l’agilité.
Poste :
Position Summary:
The UM6P Vanguard Center & The School of Applied Sciences & Engineering at UM6P invite applications for the position of Research Scientist in Data Science & Machine Learning to support the Wicked Problems (WiP) framework within our undergraduate program. The successful candidate will bring deep technical expertise and educational engagement to interdisciplinary projects requiring advanced data analysis, predictive modeling, and AI-based solutions to real-world societal challenges.
Key Responsibilities:
· Provide methodological support and design data-driven approaches for WiP student projects.
· Mentor undergraduate teams working on interdisciplinary problems involving large, complex, or dynamic datasets.
· Collaborate with teaching faculty to integrate machine learning modules into the curriculum, particularly within the WiP ecosystem.
· Co-develop tools and platforms for visualizing, analyzing, and interpreting datasets from various domains (health, agriculture, energy, logistics, etc.).
· Contribute to institutional efforts in building AI tutors, learning analytics, and knowledge graphs to enhance student experience.
· Publish research and co-author student-led publications resulting from WiP investigations.
· Contribute to applied research motivated by the WiP investigations.
Required Qualifications:
· Ph.D. in Data Science, Machine Learning, Computer Science, Applied Statistics, or a related field.
· Demonstrated expertise in supervised/unsupervised learning, deep learning, and data-driven modeling.
· Proficiency in modern ML toolkits and libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas, Jupyter).
· Experience handling diverse data types (tabular, time-series, geospatial, text).
· Strong mentoring skills and interest in education.
Desirable Qualifications:
· Experience with project-based learning or working with undergraduate students.
· Background in applied domains such as agriculture, health, manufacturing, or environmental systems.
· Interest in responsible AI, ethics in machine learning, or interpretable models.
· Familiarity with cloud-based environments or distributed computing tools (e.g., Spark, Dask, Kubernetes).
Profil recherché :
Position Summary:
The UM6P Vanguard Center & The School of Applied Sciences & Engineering at UM6P invite applications for the position ofResearch Scientist in Data Science & Machine Learningto support theWicked Problems (WiP)framework within our undergraduate program. The successful candidate will bring deep technical expertise and educational engagement to interdisciplinary projects requiring advanced data analysis, predictive modeling, and AI-based solutions to real-world societal challenges.
Key Responsibilities:
· Provide methodological support and design data-driven approaches for WiP student projects.
· Mentor undergraduate teams working on interdisciplinary problems involving large, complex, or dynamic datasets.
· Collaborate with teaching faculty to integrate machine learning modules into the curriculum, particularly within the WiP ecosystem.
· Co-develop tools and platforms for visualizing, analyzing, and interpreting datasets from various domains (health, agriculture, energy, logistics, etc.).
· Contribute to institutional efforts in building AI tutors, learning analytics, and knowledge graphs to enhance student experience.
· Publish research and co-author student-led publications resulting from WiP investigations.
· Contribute to applied research motivated by the WiP investigations.
Required Qualifications:
· Ph.D. in Data Science, Machine Learning, Computer Science, Applied Statistics, or a related field.
· Demonstrated expertise in supervised/unsupervised learning, deep learning, and data-driven modeling.
· Proficiency in modern ML toolkits and libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas, Jupyter).
· Experience handling diverse data types (tabular, time-series, geospatial, text).
· Strong mentoring skills and interest in education.
Desirable Qualifications:
· Experience with project-based learning or working with undergraduate students.
· Background in applied domains such as agriculture, health, manufacturing, or environmental systems.
· Interest in responsible AI, ethics in machine learning, or interpretable models.
· Familiarity with cloud-based environments or distributed computing tools (e.g., Spark, Dask, Kubernetes).
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