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Field
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position is available in the group of Prof. Alexey Nesvizhskii at the University of Michigan Medical School. The position will focus on developing computational algorithms and tools for the analysis of mass
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) experience in large model training, knowledge distillation or efficient deep learning algorithm development, foundation model implementation and optimisation; and (c) good communication skills in English
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, and learning capabilities Develop and optimize data-driven algorithms for anomaly detection and incident response Implement scalable, modular, and containerized solutions compatible with platforms
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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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and analytics. The post holder will develop new optimisation models and algorithms to support operational and real‑time decision making in disaster response contexts, with the aim of improving resource
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human-centred collaborative robotic systems, with emphasis on embodied intelligence and shared autonomy; (c) develop algorithms for human intention understanding, multimodal perception and fusion and
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 hour ago
. The position aims to develop novel algorithms, improve model efficiency and performance, and translate theoretical advances into practical solutions across relevant domains. The Fellow will contribute
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research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in
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on computer vision. The role involves developing and advancing novel algorithms for emerging challenges in computer vision, including continual learning and few-shot learning. The candidate is also expected
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numerical simulations of complex dynamic systems, e.g. turbulence, hurricane. The duty of the role is within the range of: 1) developing novel algorithms on data analyses and data mining, e.g. Large Models