Research Fellow: Multi-Agent Systems & Resource Allocation

Nanyang Technological University Singapore; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

NTU Singapore invites applications for research roles in its College of Computing and Data Science. The position focuses on resource allocation for distributed computing, with emphasis on multi-agent systems, path planning, and execution in complex environments.

Successful candidates will contribute to theoretical and practical advancements, test methods via simulations or real-world experiments, and evaluate performance using latency, throughput, and robustness metrics.

Qualifications

• For Research Fellows, candidates must have a PhD in Computer Science or related disciplines from a reputable university.
• For Research Associates, candidates must have a Master in Computer Science or related disciplines.
• For Research Assistants, candidates must have a Bachelor in Computer Science or related disciplines.
• Good knowledge in multi-agent systems or distributed computing, algorithm design and analysis, and optimization

Responsibilities

• Conduct research on resource allocation and distributed computing with a focus on multi-agent systems.
• Design and develop algorithms for path planning, coordination, and execution in multi-agent environments.
• Analyze theoretical aspects of distributed systems, including optimization, scalability, and efficiency.
• Implement and test proposed methods through simulations or real-world experiments.
• Evaluate system performance using appropriate metrics (e.g., latency, throughput, fairness, robustness).

Skills

Multi-agent systems

Distributed computing

Algorithm design & analysis

Optimization

Teamwork & communication

Education

PhD in Computer Science or related

Master in Computer Science or related

Bachelor in Computer Science or related

Job description

NTU Singapore invites applications for research roles in its College of Computing and Data Science. The position focuses on resource allocation for distributed computing, with emphasis on multi-agent systems, path planning, and execution in complex environments.

Successful candidates will contribute to theoretical and practical advancements, test methods via simulations or real-world experiments, and evaluate performance using latency, throughput, and robustness metrics.