124 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions in Morocco
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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
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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
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soil moisture Participate in field data collection and data analysis Satellite images processing Publish research findings in peer-reviewed journals and present results at conferences and workshops
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Polytechnic University aspires to leave its mark nationally, continentally, and globally. The School of Computer and Communication Sciences at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco is
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internationally oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development
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skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban Health Principles: Familiarity with urban planning principles centered on health (active mobility
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, reports and projects. Oral and written communication skills. Computer skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Analytical Chemistry or a related field. Extensive experience
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. Experience with data prediction and classification techniques. Computer Skills: Good proficiency with optimization tools (CPLEX, SAP). Experience with data analysis software. Soft Skills: Analytical mindset
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. The selected candidate is expected to conduct fieldwork investigations, seismic interpretation, Image Log and core logging focused on structural geology of the Meskala basin. This will involve a thorough
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical