17 bayesian-object-detection positions at King Abdullah University of Science and Technology in Saudi Arabia
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contribute significantly to the objectives outlined in Saudi Vision 2030. This alignment should be explicitly demonstrated by emphasizing one or more of KAUST's Research, Development, and Innovation (RDI
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Development Goals and to contribute significantly to the objectives outlined in Saudi Vision 2030. This alignment should be explicitly demonstrated by emphasizing one or more of KAUST's Research, Development
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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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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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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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. 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
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all aspects of these complex problems. In the Composites Lab, you will find skills ranging from theoretical mechanics, applied mathematics, and computer science to material science and chemical
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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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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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on objectives and timelines. Possibility of some remote working depending on project requirements. Additional Information: Multiple opportunities to learn and use various equipment and techniques. Availability