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across Africa using satellite remote sensing, atmospheric modeling, and deep learning. Research Focus Estimate cropland emissions (NH3 , N2 O, CO2 , CH4 ) using satellite observations, atmospheric
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Experience with machine/deep learning / AI applied to environmental or urban systems Familiarity with climate modeling, urban climate, urban agriculture, water resources, and energy systems Experience working
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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partners. Qualifications Ph.D. in Computer Science, Applied Mathematics, or a related field. Strong publication record in machine learning, with preference for expertise in representation learning, deep
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.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and
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artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize efficiency, improve safety, reduce costs and promote sustainability. Collaborate with multidisciplinary teams to uncover a
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, DeepChem, Gaussian, ORCA, ChemML). Knowledge of modern machine learning techniques (e.g., deep learning, graph neural networks, generative models). Interest in interdisciplinary research and/or real-world
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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or equivalent academic or industrial experience. Experience in handling chemical datasets and tools (e.g., RDKit, DeepChem, Gaussian, ORCA, ChemML). Knowledge of modern machine learning techniques (e.g., deep
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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