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underwater anomaly detection Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 3 Nov 2026 View more categories View less categories Discipline
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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Advancing Drug Detection and Identification for Public Health and Harm Reduction Location
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exciting future discovery is the first detection of the unknown -- sources not yet predicted by astrophysicists. Uncovering the unknown is a challenging data problem. Weak signals from collisions of
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exciting future discovery is the first detection of the unknown -- sources not yet predicted by astrophysicists. Uncovering the unknown is a challenging data problem. Weak signals from collisions of
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: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal prediction). O3: Joint OOD detection + AL: Combine
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: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal prediction). O3: Joint OOD detection + AL: Combine
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training. The Project The project aims to develop algorithms and hardware architectures for Bayesian and Ising Models that can leverage the intrinsic stochasticity of emerging magnetic random access memory
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international employees to get started In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits We welcome applications from people with diverse
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foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands-on
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 23 hours ago
King Abdullah University of Science and Technology: Researcher Positions: Computer, Electrical and Mathematical Science and Engineering Division Location KAUST Open Date Nov 30, 2025 Description This is a unified application form for all positions in the Beyesian Deep Learning group at KAUST led...