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, Intelligent_Mapping is integrated into the IRIMA Plateformes Consortium, supported by BRGM (PI: J. Langlois). The primary aim of Intelligent_Mapping is to develop Artificial Intelligence (AI) algorithms able
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computational approaches, including algorithm-guided design, sequence and structure-based analysis, epitope-related studies, and functional evaluation to support antibody development and mechanistic investigation
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are open to hearing from candidates with a wide range of critically informed expertise. This includes but is not limited to expertise in critical approaches to algorithms, AI and automation; games, immersive
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the essentials of linear algebra, calculus, probability, statistics, algorithms, and data structures. The goal is to provide a foundational understanding of machine learning and deep learning methods
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computers and developing new quantum algorithms. The division hosts a vibrant and international team of theoretical physicists, maintaining a gender balance of 40% women and 60% men, and promoting a culture
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, or related field and relevant postdoctoral research experience Familiarity with algorithms for analyzing high-throughput DNA sequencing data Familiarity with versioning tools such as GitHub Experience with
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system integration, as well as embedded controller development. Experience in modeling converter topologies and distribution grids, developing control algorithms, and implementing controller code is
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diseases and their impact on interstate and international trade and community health. They will learn surveillance procedures, diagnostic testing methodologies and algorithms, serological diagnostic methods
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Tiny Machine Learning (TinyML). The role will focus on the design and development of battery‑less, ultra‑low‑power IoT systems capable of executing secure TinyML‑based visual perception algorithms
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working with large collaborative code projects Proficiency in applying AI-driven algorithms (e.g., neural networks, reinforcement learning) for the creation of surrogate models and the autonomous