Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning committed to an educational system based
-
-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning approaches for resistome prediction or biomarker discovery is a plus. Why Join Us? Access to cutting-edge
-
analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence
-
. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
-
interplanetary travel. Autonomous Systems: Develop AI algorithms, robotics, and autonomous software to enhance spacecraft operations and exploration. Implement machine learning techniques for improved autonomy and
-
oriented institution of higher learning committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and
-
. The main objective of the project is to study the interaction between machine learning and wireless communication fields. The successful candidate will answer questions such as how to assign limited
-
embedded software for CubeSats. They will teach embedded systems and spacecraft engineering and lead experimental research on robust satellite architectures and mission reliability. Key qualifications: PhD
-
, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
-
CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, and Precision Health. The project aims to leverage AI and machine learning (ML) to analyze complex metabolomics datasets and address key health challenges, including biomarker discovery, disease