989 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" Fellowship positions
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instruments Ability to occasionally lift and move laboratory supplies or equipment weighing up to approximately 25 pounds Ability to work at a computer workstation for data analysis and manuscript preparation
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presentations at regional and national conferences will be supported. Learning Objectives: Under the guidance of a mentor, specific learning objectives include: Conducting independent research aimed at developing
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. market access. The approach will include metagenomics and bioinformatics to understand genetic diversity of the pathogen. Learning Objectives: During this project, the participant will be involved in
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software development, including Python, model integration, and system
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nowcasting platform that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes
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of design and fabrication of medical devices, 3D printing, microfluidics, mechanics of materials, biomaterials, blood-material interactions, computer aided design, and/or in vitro/in vivo evaluation