The appointees are expected to conduct independent research on federated learning systems, develop cutting-edge federated or distributed training algorithms for deep models, and write research papers for top-tier conferences or journals.
Applicants should have a PhD degree in computer science, computer engineering, or a related discipline, and sufficiently demonstrate abilities to conduct high-quality research in the areas of federated learning, distributed machine learning, parallel and distributed computing, or other related areas.
The appointees are expected to be proficient in both oral and written English. (Duration : 1 year, renewable)
Medical benefits and paid leave will be provided where applicable.
Review of applications will continue until the positions are filled.
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