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Field
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reinforcement learning and machine vision. Experience with ROS and the ROS ecosystem Special Requirements: Applicants cannot have received their PhD more than five years prior to the date of application and must
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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to support research groups associated with Institute faculty, in areas such as: ● Machine Learning and Computer Vision ● Natural Language Processing and Data Science ● Biomedical Informatics and
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to support research groups associated with Institute faculty, in areas such as: ● Machine Learning and Computer Vision ● Natural Language Processing and Data Science ● Biomedical Informatics and
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. Your competencies We imagine that you: have a background in digital signal processing and machine learning. have substantial experience with scientific computing in Python and ideally also MATLAB. have
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program is designed for candidates who have completed their PhD within the last two years and have experience as
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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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learning with a background in robust and embedded control, aerospace systems and physical modelling, as well as in artificial intelligence-related concepts, computer vision and numerical optimisation
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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