Research Fellow: AI & Multi-Agent Risk & Intervention

Singapore University of Social Sciences (SUSS); Singapore; On-site; SGD 80,000 - 110,000; Full time

Job summary

The Singapore University of Social Sciences (SUSS) invites applications for a Renewable Contract Research Fellow position in Singapore. The role focuses on designing multi-agent AI architectures for risk assessment and intervention in real-world scenarios.

You will publish in peer-reviewed venues, collaborate with government agencies, and mentor junior researchers and student teams while advancing AI research in privacy-preserving technologies.

Qualifications

• Ph.D. degree required in a relevant field.
• Strong research portfolio with publications in top venues.
• Proficient in Python and deep learning frameworks (PyTorch, TensorFlow).

Responsibilities

• Design and develop multi-agent AI architectures for risk assessment and intervention.
• Develop decision-making models for risk scoring and escalation management.
• Evaluate and benchmark agentic AI systems with real-world and simulated scenarios.
• Conduct research on AI-driven cognitive circuit breakers and localized threat detection.
• Publish research findings in peer-reviewed journals and conferences.
• Collaborate with government partners and stakeholders on project alignment.
• Mentor and co-supervise junior researchers and student teams.]
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Skills

Artificial Intelligence

Multi-Agent Systems

Machine Learning

Differential Privacy

Python

Deep Learning

PyTorch

TensorFlow

Education

Ph.D. degree in Computer Science/Engineering/Data Science

Tools

PyTorch

TensorFlow

Job description

The Singapore University of Social Sciences (SUSS) invites applications for a Renewable Contract Research Fellow position in Singapore. The role focuses on designing multi-agent AI architectures for risk assessment and intervention in real-world scenarios.

You will publish in peer-reviewed venues, collaborate with government agencies, and mentor junior researchers and student teams while advancing AI research in privacy-preserving technologies.