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designed to facilitate a timely transition of outstanding postdoctoral researchers with a research and/or clinical doctorate degree from mentored, postdoctoral research positions to independent, tenure-track
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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tracking/monitoring, blockchain Biotechnology: Host strain screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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to revolutionize the research field in 3D learning. Research topics include: - Neural Rendering: 3DGS, NeRF, etc. - Generative AI: Diffusion, LLMs, GANs, etc. - 3D Reconstruction - SLAM / Pose Tracking (SfM, MVS
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disciplines (typically mathematics, physics). For Postdocapplicants: Excellent track recordin computer science or engineering. Fluency in spoken and written English is required. Proficient in at least one
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campus faculty governance. Perform other job-related duties as assigned. FAU Benefits and Perks This position is a non-tenure-track faculty position at the rank of Associate University Librarian on a 12
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– 57k Euro / year + benefits). Topics include: Neural Rendering, 3D Reconstruction, SLAM / Pose Tracking, Semantic Scene Understanding, Face/Body Tracking, Non-Linear Optimization, Media Forensics / Fake
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12 months), either to accept or to continue with a tenure-track teaching appointment but for no other reason. Academy Scholars may not accept other sources of funding, awards, or obligations during