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Job Description The successful candidate will work with Professor Mark Breese on Intelligent computer vision algorithms under a project on “Development of Cone Prism Camera Technology”. We seek a
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Job Description The successful candidates will contribute to research activities related to use of computer vision, machine learning, and analytics to construction safety. The candidate shall work
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Job Description The successful candidates will contribute to research activities related to developing computer vision systems to improve construction site safety. The candidates shall work under
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Job Description The successful candidates will contribute to research activities related to developing computer vision systems to improve construction site safety. The candidates shall work under
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or interest in at least one of the following research areas: Artificial Intelligence and Machine Learning Computer Vision Econometrics Causal Analytics Programming Languages & Software Engineering Only
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publications. • Proficiency with LiDAR or computer vision, including open-source frameworks and algorithms for 3D scene reconstruction. • Experience in Python programming (At least one year of experience
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publications. • Proficiency with LiDAR or computer vision, including open-source frameworks and algorithms for 3D scene reconstruction. • Experience in Python programming (At least one year of experience
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, optimization, algorithms, computer vision, artificial intelligence, data science, software development, drone development or embedded system development. Ability to work independently as well as in teams and
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the mathematical workings of common algorithms for computer vision/NLP/tabular data. Hands-on skills in Python-based AI/ML frameworks, specifically LangChain, LlamaIndex, TensorFlow, PyTorch, Keras, and scikit-learn
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the mathematical workings of common algorithms for computer vision/NLP/tabular data. Hands-on skills in Python-based AI/ML frameworks, specifically LangChain, LlamaIndex, TensorFlow, PyTorch, Keras, and scikit-learn