151 Design-"https:" "https:" "https:" "https:" "https:" Fellowship positions in Singapore
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Schemes of Service: Research Division: Professional Officers Employment Type: Fixed Term Innovation-as-a
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within the Physical Vision Group (PVG, https://physicalvision.github.io/ ). This will involve closely collaborating with faculty, postdoctoral researchers, and PhD students, bridging foundational
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking a highly motivated Research
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of project milestones, technical outputs, and reporting requirements. Design and conduct experimental programmes for ultra-low carbon concrete systems, including LC3- and steel slag-based materials, as
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, 3D PCA, or other dimensionality reduction methods for integrating complex, multimodal datasets. Experience working with limited sample volumes, and ability to design robust experimental protocols
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: Fixed Term Job Purpose The Senior Research Fellow/Research Fellow for Design Factory will play a pivotal role in identifying opportunities and problems that others choose to ignore and solve it with
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traversal tasks. Support calibration, perception, locomotion, manipulation, and control pipeline integration. ii. Experimental Testbed Development Design and set up representative door interaction
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education, contributing to broader efforts to improve healthcare through evidence generation. For more details, please view https://www.ntu.edu.sg/medicine/research/office-of-patient-engagement-(open) . We
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responsibility of this role is to deliver an industry innovation research project as part of a research team developing molecular and sequencing workflows for microbial characterization. The work supports the
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow in Multi-Agent RL for Autonomous Drone Swarm to develop learning-based