180 image-processing-postdoc "https:" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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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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in POD, they jointly develop central policies and processes for the safe and seamless operation of laboratories in SIT. Key Responsibilities Design and teach labs & practice modules. Mentor students in
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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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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
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cluster moulds electronic and computer engineers, computer scientists, AI engineers, interactive media and game development experts, software engineers, and information security specialists. We invite
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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 work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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models to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control. You will contribute to both the backend development (pipeline orchestration
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of movement quality after stroke using multimodal functional brain imaging and 3D human kinematics. This funded research brings together multidisciplinary expertise from Singapore Institute of Technology (SIT
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models to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control. You will contribute to both the backend development (pipeline orchestration