93 phd-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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materials such as the magnetoelectric, high entropy oxides, through neutron scattering experiments. Additionally, collaborative work will be performed with the aim of developing and applying machine learning
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wonderful place to live. Visit the Maine Office of Tourism to learn more about what the Bangor region has to offer. Qualifications: Required: PhD degree in a relevant science (behavioral and human sciences
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previous experience; ability to write papers for peer-review on technical topics related to architectural design and machine learning and conduct grant research; as normally acquired through a PhD in
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integrated circuits (IC) and printed circuit boards (PCB). Additionally, the candidate should demonstrate expertise in applying computer vision, image analysis techniques, machine learning, deep learning to IC
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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to solve biomedical problems, or a PhD in biomedical sciences with a strong interest to apply AI and machine learning approaches. With our strong commitment to translating research findings to actionable
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software skills in C++, python. Understanding of computing software development in the HEP environment, familiarity with machine learning (ML) techniques and experience with using ML software packages (e.g
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI