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: 87645BR Supervises staff involved in providing clinical patient care. Assists in ensuring the quality of patient care delivery in a specific patient care area and serves as a role model for professional
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itself by the use of materials, orientation and type of buildings, or the influence of vegetation. Project description The candidate will focus on the urban environment and develop a model to predict the
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characterization platform for innovative materials by combining advanced experimental techniques, physics-based mesoscopic modeling, and artificial intelligence. Within this context, high-throughput experiments and
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& instructional materials for different learning styles incorporating, as pedagogically appropriate, current technology in classroom, distance learning and laboratory environments creating and modeling a quality
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produced under conditions representative of rocket engines, for a selection of metals. After meticulous experimental characterization, the unique database obtained will be exploited to enhance the modeling
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Sorbonne Universite - Laboratoire de Chimie de la Matière Condensée de Paris (LCMCP) | Paris La Defense, le de France | France | about 2 hours ago
5 Apr 2026 Job Information Organisation/Company Sorbonne Universite - Laboratoire de Chimie de la Matière Condensée de Paris (LCMCP) Research Field Technology » Materials technology Biological
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to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across
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materials synthesis and growth, characterization, novel probe development, and theory; 2) Modeling in order to enhance computation technology; 3) Modeling the behavior of skyrmion magnetic interfaces; and 4
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and will contribute to key modeling and simulation deliverables for drug candidates across early and late stages of clinical development, spanning multiple therapeutic modalities. The Fellows will
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Research Scientists as part of its new initiative, Polymathic AI, Building Foundation Models for Science. Recent advances in machine learning, including Large Language Models and diffusion based generative