Sort by
Refine Your Search
-
researchers and PhD students, and strong national and international collaborations, MSN is a growing force in materials research. Job Description Postdoctoral Researcher in Mineral Processing, Battery Materials
-
15 Jan 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
-
seeking a highly motivated postdoctoral researcher holding a PhD in Zootechny, Animal Nutrition or Pastoralism to join its Animal Sciences team and contribute to the development and implementation
-
related to the project. Candidate Profile Strong proficiency in software tools related to materials/process modeling, thermochemical systems, statistical design (DoE), and data analysis. Excellent verbal
-
, cooperatives, extension agents, etc. Data scheduling, collection, analysis, interpretation, and presentation. Co-supervise PhD and Master students as well as interns Project management including budget
-
-based data collection and integration, fieldwork, mineralogical and geochemical characterization (gypsum, anhydrite, native sulfur). Ability to engage professionally with a diverse population of faculty
-
22 Jan 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Environmental science Geosciences Researcher Profile Recognised Researcher (R2) Established
-
, and synthesize experimental data to support process development; Contribute to the economic and environmental assessment of developed processes; Prepare technical reports, research papers, and
-
contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
-
valorization and pilot process design is a strong asset. Proven publication record and project involvement. Additional Skills (Preferred): Experience with environmental data analysis (R, multivariate statistics