342 algorithm-phd-"Prof"-"Washington-University-in-St"-"Prof" Fellowship positions in Singapore
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. Develop and enhance advanced optimization algorithms for the Energy Management System (EMS), addressing energy dispatch, storage control, load scheduling, and strategies for market participation. Architect
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on high-speed vision perception for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries
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Analytics & Explainability development of algorithm and system for the project The School of Computing at the National University of Singapore (NUS) invites applications for a Postdoctoral Research Fellow
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duties Job Requirements: PhD in Optical/Device Physics, Electrical Engineering, Materials Science, or a related field with low-dimensional nanophotonics. Excellent publication records will be preferred
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the research project • For those hired at senior levels, management responsibilities may be included Qualifications • Have a PhD degree in Electrical Engineering or equivalent from a recognized University
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algorithms, and innovative mechanical design to replicate the remarkable flight capabilities observed in nature. The successful candidate will be part of a dynamic, multidisciplinary team of experts in
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instructing or supervision of labs and tutorials. Prior teaching experience is preferred for candidates. It would be good if the candidate can also explore areas such as multimodal algorithms/techniques
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Responsibilities: Undertake research on algorithms and data systems for next-generation data preparation and data cleaning for data analytics. Produce research papers, reports, and presentations as required by
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(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes