Research Assistant: Scalable AI/HPC Systems

ntu

Singapore

On-site

SGD 42,000 - 72,000

Full time

5 days ago
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Job summary

Nanyang Technological University, Singapore (NTU Singapore) invites applications for a Research Assistant/Research Associate to join the Parallel Systems Lab within CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI workflows.

The RA will perform workload analysis, system prototyping, benchmarking, and experimental validation on local and national supercomputing platforms, collaborating with faculty and domain scientists to

Qualifications

  • Bachelor's or master's degree in Computer Science or a related discipline.
  • Strong knowledge of agentic AI/AI workflows, parallel computing, algorithms and system performance analysis.
  • Proficiency in programming languages such as C/C++ and Python.
  • Demonstrated ability to conduct research and develop innovative solutions.

Responsibilities

  • Analyze and characterize emerging multi-agent AI and HPC workloads to identify performance, scalability, and system-level challenges.
  • Design, implement, and prototype efficient systems and infrastructure for large-scale AI/HPC workflows.
  • Conduct benchmarking and experimental evaluation on local and national supercomputing platforms, analyzing performance and scalability.
  • Contribute to research papers, technical reports, and presentations for internal reviews and external conferences or journals.

Skills

Analytical thinking
Independent work
Communication skills

Education

Bachelor's or Master's in Computer Science or related discipline

Tools

C/C++
Python

Job description

Nanyang Technological University, Singapore (NTU Singapore) invites applications for a Research Assistant/Research Associate to join the Parallel Systems Lab within CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI workflows.

The RA will perform workload analysis, system prototyping, benchmarking, and experimental validation on local and national supercomputing platforms, collaborating with faculty and domain scientists to

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