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seeking a postdoctoral candidate in the area of federated learning and wireless communications. The candidate must hold (or about to complete) a PhD in the related fields. The candidate will be involved in
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Polytechnic University (UM6P), Benguerir, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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The successful candidate will contribute to the following research axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate
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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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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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techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics. Responsibilities of the Position The Postdoctoral researcher is intended to support the soil spectroscopy research activities and digital
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation