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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling
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Mathematics, Control Theory, Dynamical Systems, Partial Differential Equations, Algebraic Geometry, Quantum Algorithms, and Information Theory Application Fields: Biological Systems, Agriculture, Epidemiology
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, Master and PhD levels to establish a vibrant program of teaching at the interface between geology and mineral resources. Experience in the acquisition and/or management of third-party funded projects along
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, and master's courses. Develop innovative modules based on collections and multidisciplinary research. Supervise MSc and PhD students to develop a pool of high-level palaeontologists. Support the
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. Prepare and submit high-impact scientific publications and present results at international conferences, workshops and meetings. Mentor master’s and PhD students as part of research activities. Collaborate
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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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(UM6P-FMS), the Cluster's main institution, endeavors to build very high-level medical and paramedical study programs. UM6P-FMS aims to train medical doctors, PhDs, pharmacists and nurses in a scientific
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of the PhD thesis, A statement of research and teaching interests and plans, Written references from 2 persons or contact details for them, Other documents that the candidate considers important for
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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