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- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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NTU, CEE is a leading school for Sustainable Built Environment. We are looking for a research fellow to support the development of algorithms for anomaly detection, simulate and test it on
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of novel edge-assisted computation offloading strategies that leverages edge intelligence. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core
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will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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algorithm code base including noise reduction, acoustic echo cancellation, automatic gain control, voice activity detection, packet loss compensation and other audio enhancements Software development of new
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sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation, localisation, path planning, and collision avoidance algorithms
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algorithms for mobile robots. Implement and accelerate visual algorithms for mobile robots on embedded platforms. Develop a visual embedded platform on a mobile robot. Conduct field trials with the robotic
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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high-frequency ultrasound imaging platform, including hardware-software integration and advanced signal processing algorithms for structural and functional imaging, in order to deliver clinically
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Develop novel methods and algorithms for the verification, testing and robustness analysis