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of methods for anomaly detection and disease recognition based on learned normative representations • Development of vision-language models for clinical reasoning and interpretable reporting of medical imaging
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transportation systems and autonomous driving. • Strong understanding of generative AI, deep learning, and multimodal machine learning, with hands-on experience. • Excellent programming skills and proficiency with
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
position will include, but is not limited to, multimodal+embodied semantics, human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning. The duties of the postdoctoral
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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
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to participate in research and teaching. While research and participation in the intellectual life of the program is the primary responsibility, the postdoctoral research associate will be expected to teach one
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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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Posting Details Position Details Title American Religion Postdoctoral Scholar Appointment Status Non-Tenure Track Department IU Bloomington Center Religion and the Human Location Bloomington
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework