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focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction
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recently completed (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
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. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected to have hands-on experience in field related to urban or rural planning, renewable
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to teaching activities or other transversal training. Disseminate research outcomes through participation in scientific events and publish in leading international journals. Desired skills and experiences: PhD
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methods. The interest areas are (but are not limited ): to novel electronic structure and methods, light-matter interactions modeling, topological phenomena, magnetism, superconductivity, quantum
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separation and magnetic phenomena, as well as expertise in experimental methods to study the interactions between magnetic fields and solid and liquid materials. Additionally, knowledge of the physical and
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security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning
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of the candidate: PhD in atmospheric sciences or a closely related field The candidate should have experience in climate model development and assessements A strong programming background and use of HPC are required
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, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their
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, Polymers and Composites, and Sustainable Materials. With some 100 researchers and PhD students and several national and international partners, MSN is emerging as a strong actor in the Moroccan materials