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Field
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Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will be advantageous. Key Competencies Prior experience in research project coordination and
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) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5, Franka Emika
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stakeholders, end users, industry partners, and multidisciplinary research teams to support system integration and project delivery. Preferred Skills Python, C++, ROS/ROS2. Computer Vision (OpenCV, Deep Learning
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Evidence of research achievement at the very highest international level, including a strong record of publications in top-tier venues in AI/machine learning and evidence of significant influence
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that machine learning applications are developed with ethical considerations in mind. Participate in regular meetings with the research group. Required Qualifications* Ph.D. in Electrical Engineering, Computer
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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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the last 60 months or anticipated to be received by 10/1/2026 12:00:00 AM. Discipline(s): Chemistry and Materials Sciences (7 ) Computer, Information, and Data Sciences (10 ) Earth and Geosciences (9
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life Health and Medical Sciences (51 ) Mathematics and