960 machine-learning-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" Fellowship positions
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such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
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Fellow will help mentor undergraduate students, work with Center for Health Research staff and will have the opportunity to teach classes by separate assignment as a part-time lecturer. This position will
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Innovations Group seeks a forward‑thinking expert in statistical machine learning to translate complex biological datasets into actionable AI‑driven insights. You will enhance genomic selection and breeding
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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the devastating disease avian coccidiosis. The secondary goal is to compare various Eimeria spp. to identify genes involved in intestinal cell specificity, virulence, and markers of drug resistance. Learning
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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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of the opportunity involve various outdoor conditions requiring moderate exertion and traversing the landscape of the MEF. Additionally, the fellow will experientially learn about and participate in the Forest Service
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. Mentorship will include advancement in time motion and management of a practice. Fellows will learn to work with and lead the entire dental team while providing services to patients with a variety of needs
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emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can
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intelligence that coordinates the entire experimental ecosystem. The Postdoctoral Fellow will develop agentic AI models and frameworks for intelligent experimental workflows, which couple machine learning, real