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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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short-horizon forecasting and patient-specific rebasing; implement data-assimilation methods (Kalman/Bayesian updating); design anomaly detection and missing-information inference logic. 40% Software
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 16 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...
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data, Bayesian statistics, random object analysis, and optimal transport. Experience with neuroimaging data processing and analysis is a plus. The fellows will work with an interdisciplinary team
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contact-rich, deformable object, and multi-object manipulation, and data-efficient adaptation to new tasks and embodiments. 2. Fault prediction and reliable autonomy : data-driven condition monitoring
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implementing signal-processing tools for the detection, classification, localization, and density estimation of marine mammal acoustic signals; developing and implementing underwater acoustic
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imaging modalities Experience in one or more of the following areas: object detection and segmentation, multi-object tracking, time-series analysis, probabilistic modeling and uncertainty quantification
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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-rich, deformable object, and multi-object manipulation, and data-efficient adaptation to new tasks and embodiments. Fault prediction and reliable autonomy : data-driven condition monitoring
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, GIS, or environmental exposure modeling. Demonstrated experience with Bayesian modeling, simulation methods, machine learning, or uncertainty analysis. Demonstrated leadership in research design