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and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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the student recruitment process. Once interest is confirmed, reinforce the student's decision by highlighting the benefits of joining the LeTourneau community and the Christian Polytechnic University. Provide
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Institution Overview Mohammed VI Polytechnic University is a leading research and innovation institution in Africa, committed to economic and human development. The university places research and
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Institution/Department Mohammed VI Polytechnic University Chemical & biochemical sciences.green process engineering Research Unit on Microbiome and Host-Pathogen Interactions Project Overview: We
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experience at the time of application; (b) have experience in InSAR applications for landslides and reclamations, PolSAR/PolInSAR for vegetation mapping, finite element analysis, numerical simulation, machine
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(especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. Knowledge of complex systems
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The Hong Kong Polytechnic University Position ID: 1437 -AMA250210008 [#26287] Position Title: Position Type: Non tenure-track faculty Position Location: Kowloon, Hong Kong [map ] Subject Areas
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, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
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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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activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural