Research Fellow (Computer Science/Electrical& Electronic Engineering/Mathem at NANYANG TECHNOLOGICAL UNIVERSITY
Singapore, , Singapore -
Full Time


Start Date

Immediate

Expiry Date

28 Nov, 25

Salary

0.0

Posted On

28 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Mathematics

Industry

Information Technology/IT

Description

The Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) represents a key collaboration between Alibaba Group and Nanyang Technological University (NTU). Supported by the Singapore RIE2025 Fund, ANGEL creates and deploys impactful green digital technologies for global sustainability.
ANGEL’s mission aligns seamlessly with Singapore’s national objectives, such as the Singapore Green Plan 2030 and the Singapore Smart Nation Initiative. ANGEL’s work in developing sustainable and equitable digital solutions and promoting a sustainable and green lifestyle will contribute to a smaller carbon footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity.

Key Responsibilities:

  • Conduct independent research in the field of federated learning, focusing on incentive mechanism design.
  • Help supervise PhD, master and undergraduate students, and R&D staff.
  • Help with federated learning technical platform design and development.
  • Help with collaboration with existing industry partners.

Job Requirements:

  • PhD degree in Computer Science/Engineering, Electrical/Electronic Engineering, Mathematics or other related disciplines from a reputable university.
  • Good publication track record is a must.
  • Previous research experience in explainable AI related fields preferred.
  • Previous research experience in the field of federated learning will be advantageous.

We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU

Responsibilities
  • Conduct independent research in the field of federated learning, focusing on incentive mechanism design.
  • Help supervise PhD, master and undergraduate students, and R&D staff.
  • Help with federated learning technical platform design and development.
  • Help with collaboration with existing industry partners
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