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Engineering, or related field. • Demonstrated expertise in deep learning and AI methodologies. Experience in medical image analysis, particularly applied to cancer research (pathology, MRI, CT scans) preferred
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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structures and corresponding images) needed for training and validating deep learning (DL) models. Work closely with members of the ICMN nanostructures group or external collaborators. Communicate research
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
. Throughout the Fellowship, individuals will have the opportunity to participate in research using digital pathology, machine learning, deep learning, artificial intelligence, and digital image analysis. Other
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Project Overview The DiSTAP programme addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic and biosynthetic
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strong background in shape modelling, deep generative modelling (diffusion/transformers), or multimodal representation learning. You have strong programming skills, especially in Python, and preferably
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School of Medicine Indianapolis Position Summary Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging
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electrophysiology. We are seeking a postdoctoral researcher to lead the neuroimaging component of a longitudinal, pediatric drug trial in Neurofibromatosis type 1 (NF1). In this role, you will acquire and analyze
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processing, artificial intelligence, cognition and deep learning, machine learning, navigation and mapping, autonomous driving, assistive robotics, drones, dynamics and vibration, acoustics, medical imaging