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Scholar with strong expertise in computer vision, multimodal AI, machine learning, and/or agentic AI to help build the next generation of intelligent digital health solutions. You will work side by side
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large-scale human data (genomes, single-cell and spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s
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Details Title Postdoctoral Fellowship Position in Visual Computing at Harvard University School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Sciences
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autonomous robots for field use and has tested them in mines and other underground environments. We are now looking for a postdoctoral researcher to develop autonomy for teams of legged, wheeled and
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., near-miss detection, predictive crash risk, multimodal exposure estimation). · Design, implement, and validate AI pipelines (computer vision, tracking, spatio-temporal modeling, edge learning
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University of New Mexico’s Center for Advanced Research Computing (CARC), within the Department of Computer Science, seeks a full-time Postdoctoral Researcher to lead development of an open-source
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Details Title Tenure-Track Professor in Electrical and Computer Engineering School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Electrical and Computer
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Investigation. November 14, 2019. DOI Keywords Artificial Intelligence; Computer Vision; Confidence Estimation; Eligibility citizenship Open to U.S. citizens level Open to Postdoctoral applicants Stipend Base
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Zhixiang Chen is a Lecturer (Assistant Professor) at University of Sheffield. Previously, he was a Postdoctoral Research Associate at Imperial Computer Vision and Learning Lab of Imperial College London
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PhD Position - Efficient Long-Context Large Models for Vision and Vision-Language-Action Systems ...
Helmholtz Association of German Research Centres | Karlsruhe, Baden-Württemberg | Germany | 2 days agoautonomous systems. You will investigate efficient long-context models for computer vision and VLA systems and apply it to autonomous driving. The research will combine attention optimization, token