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aspects of computational modelling, brain-computer interface technologies as well as within NUS focusing on design and application from the lens of landscape architecture. The research assistant to be hired
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health assessment through visual behavior recognition, image-/video-based analytics, and biosignal interpretation (e.g., growth rate estimation, movement, coloration). Design and implement experiments
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to disaster events, and mapping ocean colours and ocean topography for carbon flux estimates. We are also interested in candidates who have experience applying machine learning to InSAR and other remote sensing
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holder is preferred Background in cognitive science, psychology, human computer interaction or AI system design is preferred Further information about the University and the School can be viewed
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, Mechanical Engineering, Electrical & Computer Engineering, Mechatronics, or related disciplines. • Demonstrated excellence (or strong potential) in undergraduate and/or graduate-level teaching, particularly
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to detail; Have knowledge of computer applications, e.g. MS Office Suite/Office 365, GraphPad Prism, Python and/or R programming 3.2 Experience : One year (or more) of relevant laboratory research
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learning and computer vision frameworks. Good written and oral communication skills. Proficiency in machine learning algorithms, visual perception techniques, Python, and pytorch. Interpersonal skill (e.g
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its potential contribution to savings based on its contribution to clinical and public health decision making. Additionally, this work will require generating estimates of demand for genomics across
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. Write the report for the project progress. Work with research assistant for the prototype. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field
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publications in CAV/traffic modelling, computer vision, or reinforcement learning. Hands-on with YOLOv8 + DeepSORT and RL platforms (e.g., FLOW) for traffic control. Excellent English communication - essential