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, including design approaches, scanning methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system
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will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI
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detection of microbial bioburden in biopharmaceutical cleaning validation processes. The role involves aptamer discovery, nanomaterial-based SERS sensor development, and integration with microfluidic systems
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foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands
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and take ownership of work Interest in AI, machine learning, image/audio processing Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408369/research-engineer-r… Requirements
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variants, EfficientNet, ResNet, U-Net) Image processing and computer vision techniques Python programming and relevant libraries (e.g., OpenCV, NumPy, scikit-learn, Pandas, Matplotlib) Experience with
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, including design approaches, scanning methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system
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will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI
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-vision-based quality inspection in manufacturing plants. The system will enable users to drag and drop foundational AI models to build customized AI pipelines for tasks such as image enhancement, detection
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI