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devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
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at conferences, and stakeholder engagement sessions. Required Qualifications: A Ph.D. in Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in
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aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in
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energy applications (domestic energy consumption, electric vehicles, smart buildings). • Proficiency in optimization techniques (mathematical algorithms, heuristics, or machine learning) applied
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machine learning, particularly deep learning and natural language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency in Python and relevant
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learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A successful post-doc candidate will work with a professor of the College
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machine learning, particularly for multi-variable simulations. • Knowledge of complex systems modeling applied to urban dynamics. • Publications in scientific journals. Personal and Organizational
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Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural language processing. Experience with transformer
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: Experience in developing smart city models focused on health and environmental infrastructures. • Advanced Data Analysis: Advanced skills in machine learning, deep learning, and advanced statistics
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) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily intended to support leaf spectroscopy research but will also be involved in other research