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-prof-… Requirements Additional Information STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail
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Assistant Professor in Africa Cities and Environment Mohammed VI Polytechnic University - Benguerir - Morocco About UM6P: Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system based on the highest...
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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
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over Morocco. Key Responsibilities: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation and temperature in
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as is often the case in sparse tensor and matrix operations. Therefore, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms
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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems , security and computational materials science. Description of the position and
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. Proficiency in programming MATLAB and Python for data analysis and algorithm development. Knowledge of data assimilation techniques is a valuable added. Excellent communication skills and ability to work
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, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state
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. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized