Sort by
Refine Your Search
-
infrastructure, has woven an extensive academic and research network, and its recruitment process is seeking outstanding academics and professionals to promote Morocco and Africa’s innovation ecosystem. About the
-
quantum dots for downconversion mechanism. Candidates should have demonstrated experience and hands-on expertise in chemical synthesis, functionalization, characterization, thin-film processing of colloidal
-
English is a requirement. Excellent communication and interpersonal skills. High motivation and interest in scientific work Applications and selection procedure: Application folder must contain: Cover
-
and selection procedure: Application folder must contain: Cover letter indicating the position applied for and the main research interests. Detailed CV. Brief research statement. Contact information
-
Assistance in the teaching activities as a team member of biomass valorization program at UM6P-ASARI, to support courses related to: Food technology (for farmers). Biorefinery Technology Instrumental process
-
remotely sensed data. The center’s research aims to improve the understanding of surface processes and their interactions with climate and human activities, with an emphasis on the sustainable management
-
remotely sensed data. The center’s research aims to improve the understanding of surface processes and their interactions with climate and human activities, with an emphasis on the sustainable management
-
and Analysis: Conduct high-quality, independent research in food product quality, processing, and safety; Analyse, interpret, and document complex research findings to advance the field of food
-
spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
-
language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). Experience with