44 postdoc-image-processing Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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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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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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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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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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, 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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welcome to apply. Familiarity with image data analysis tools such as SPM, FSL, AFNI, and/or DSIStudio etc will be an advantage. Signal processing and programming skills (e.g. with Matlab, Python) will be
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, emulations, physical testbeds, and commercial networks. Collect and analyze KPIs such as throughput, latency, and reliability, and fine-tune network parameters to meet diverse QoS requirements. Prototype and
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, emulations, physical testbeds, and commercial networks. Collect and analyze KPIs such as throughput, latency, and reliability, and fine-tune network parameters to meet diverse QoS requirements. Prototype and
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development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One year for every year of sponsorship. Application Process
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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