80 phd-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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Mohadeseh Taheri-Mousavi’s group. The postdoc will develop and conduct advanced machine learning techniques combined with computational research to study the mechanical behavior of welds. Responsibilities
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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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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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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work will focus on problems in controls, machine learning, image reconstruction, wavefront sensing, and instrument development and test. As time permits, you will be encouraged to conduct your own
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, the Associate will assist with research and development projects in the areas of robotics, machine learning, control systems, and/or computer vision. They will be responsible for: designing and analyzing
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profiles, to identify treatment response patterns, subtypes, and critical intervention windows that reduce Alzheimer's risk Disease (AD) risk. This position will involve applying machine learning, deep
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
research vision. Minimum Education and Experience Requirements PhD in Biomedical Engineering, Neuroscience, or a closely related field. Required Qualifications, Competencies, and Experience Previous research
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statistical analysis and computer programming in any of the following areas are highly valued: structural equation modeling, mixed effects modeling, mediation analysis, spatial modeling, web-based mapping