102 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"The-Francis-Crick-Institute" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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Role Overview As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have opportunities to tackle real-world, industry-relevant
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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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by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Role Overview As a University of Applied Learning, SIT works closely with industry in our
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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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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning and the third largest university by intake in Singapore. Our mission is to maximise the potential
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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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