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Field
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cutting edge technologies in robotics and AI (Autonomous Robots, SLAM, Navigation, Perception, Human-Brain Interface, Deep Learning and their Security, etc.). CAIR has state of the art autonomous unmanned
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tools that help to solve an environmental challenge Growing as a scholar (20%) Working closely with our team of data scientists and software engineers and finding ways to both learn from their approaches
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with electronic health record (EHR) and/or clinical data. Proficiency in Python, with strong coding and debugging skills. Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow
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or prior experience with multilingual or low-resource NLP Programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and their application in high-performance
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communication and collaborative skills. Experience with SLAM, sensor fusion, LiDAR/depth camera data processing. Familiarity with deep learning for obstacle avoidance (e.g., map-less navigation). Background in
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, deep learning, and data analytics will be beneficial. 4. Experience in Dynamo programming would be preferred. Willing to learn and responsible. 5. The appointed candidates will support the planning
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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weekly working time of 40 hours per week. The position can be filled on a part-time basis. Background: Addressing climate change and biodiversity loss requires a deep understanding of global land-use
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learning, or deep learning models Salary Information Commensurate with experience Review Date March 10, 2025 Additional Information The successful candidate will be required to have a criminal conviction
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skills. Excellent programming skills in Python and Julia with experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Experience building complex software systems, preferably with industry