18 bayesian-object-detection positions at King Abdullah University of Science and Technology
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○ Object Detection: YOLO family (v5, v7, v8, v11), Faster R-CNN, RetinaNet ○ Image Processing: Classical and deep learning-based approaches ○ Version Control: Git ○ ML Operations
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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stakeholders, the role ensures high-quality curriculum design, alignment with emerging technologies, and impactful program outcomes that contribute to national talent development and lifelong learning objectives.
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tasks require high-frequency evaluations of forward models, in order to quantify the uncertainties of rock and fluid properties in the subsurface formations. Therefore, the objectives of this research
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divisions. Furthermore, we expect research proposals to align closely with the UN Sustainable Development Goals and to contribute significantly to the objectives outlined in Saudi Vision 2030. This alignment
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-7 cleanrooms and related laboratory safety systems, including hazardous gas detection, emergency response protocols, exhaust systems (toxic, corrosive, and heat), general abatement and spill control
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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; Experience of working in an international environment is desirable. Apply now » Find similar jobs: KAUST Jobs, Academic and Research Jobs Careers Home View All Jobs Main KAUST website Privacy Notice
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; Experience of working in an international environment is desirable. Apply now » Find similar jobs: KAUST Jobs, Academic and Research Jobs Careers Home View All Jobs Main KAUST website Privacy Notice
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and