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Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department of Physics, City
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences
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deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research of integration of multimodality data with clinical, radiological images
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms; implementing and testing ROS nodes
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, and sensor data processing algorithms; implementing and testing ROS nodes, embedded controllers, and closed-loop control routines on prototype hardware; preparing technical reports, delivering
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. Applicants should possess a PhD degree in Biomedical Sciences, Biochemistry, Chemistry or a related discipline. They should have strong background and research experience in at least one of the following areas
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the possibility of renewal subject to satisfactory performance and funding availability. Applicants should possess a PhD degree in Biomedical Sciences, Biochemistry, Chemistry or a related discipline. They should
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or the Director of the Museum Studies Programme or the PI. Applicants must have a PhD degree in Chemistry, Material Science and Engineering, Physics, or related disciplines, or in Conservation/Heritage