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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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objects and segmentation models for a robotic pick and place project. Develop data augmentation/data synthesis methods to address challenges from limited training data. Develop algorithms to annotate 2D
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, research staff, and/or postdocs, as well as mentoring junior faculty. Experience in leadership and/or service roles. SoH has a diverse and inclusive workforce and is committed to equality of opportunity. We
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NTULearn for all MSc programmes. Coordinate Student Feedback on Teaching (SFT): preparation, distribution, and compilation. Provide event support for programme-level activities and student engagement
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Prepare matriculation and distribution of matric cards for incoming students Programme Operations: Academic Services Prepare timetables of classes and examinations Prepare attendance lists of the modules
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” wherein messages including emotions are incorporated into the movements of collaborative robots. Key Responsibilities: Design, implement, and test real-time multi-objective motion planning algorithms
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relevant publications in reputable peer-reviewed international journals Demonstrated the ability to obtain extramural funding A good track record of supervising research staff, postdocs, students, and
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to simulate the spatial distribution of air pollutants in a city at a high spatial resolution. The model development requires to collect data at different aspects. The position will have to work on the data