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responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to design, develop and evaluate schemes for quantum key distribution networks and
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Intelligence (AI) services in Internet of Things (IoT) networks, where latency and timeliness are paramount. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted
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the Infocomm Technology cluster at SIT. This project addresses the critical challenge of delivering real-time Artificial Intelligence (AI) services in Internet of Things (IoT) networks, where latency and
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combined with AI-based modification on speech signals. The need is for a real-time system, so efficient coding is important. Key Responsibilities: Participate in and manage the research project with
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, AI-assisted explainability. The need is for a real-time system, so efficient coding is important. Key Responsibilities: Participate in and manage the research project with Principal Investigator (PI
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algorithms. Design and develop robust Python APIs for edge-only, cloud-only, and edge-cloud computation offloading algorithms. Set up network testbeds integrating hardware, software, and communication
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-cloud computation offloading algorithms. Set up network testbeds integrating hardware, software, and communication protocols to validate edge-only, cloud-only, and edge-cloud computation offloading
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efficient coding is important. Key Responsibilities: Participate in and manage the research project with Principal Investigator (PI) Ian McLoughlin, Co-PI Tong Rong and the research team members to ensure all
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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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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as ANSYS package