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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
important reason why Carolina is one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans. You will be responsible for the design and testing of original machine-learning based methods for fetal heart
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and qualifications Expertise in advanced machine learning, deep learning and image vision techniques with focus on EO data (e.g. deep convolutional neural networks, transformers, deep learning based
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Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived
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. The project will involve drone optimizations, computer vision, closed-loop control, multi-modal sensor fusion, machine learning, and transfer learning methods. The candidate will also work in collaboration with
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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at the interface between mechanics and machine learning? We are looking for a postdoctoral researcher for a fixed term, full time position at the Department of Materials and Production on Aalborg campus, starting 1
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. Desired Qualifications (at least one): Primary authorship in top-tier AI, machine learning, data science, computer vision, natural language processing, knowledge representation, statistics, applied
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data