38 computational-model Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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team to lead the storm surge modelling in the Singapore Sea. As a specialist in wave modelling software, the successful candidate will work on cutting-edge projects related to coastal and ocean wave
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) Application Deadline 22 Apr 2026 - 00:00 (UTC) Country Singapore Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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offloading for public safety services. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted computation offloading strategies that leverages edge intelligence
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May 2026 - 00:00 (UTC) Country Singapore Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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physical model tests in wave basin to validate computational models. Analyze experimental data to improve and validate the floating breakwater design. 6. Research Documentation and Dissemination: Prepare