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Location
In office (Singapore)
Seniority
Principal
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 6, 2026. Nanyang Technological University scores B on the Alion truth index.

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Nanyang Technological University is a public research university in Singapore with colleges of engineering, science, business, humanities and medicine, the latter run jointly with Imperial College London as the Lee Kong Chian School of Medicine. It also houses the National Institute of Education, which trains the country's teachers, and runs research centres in areas such as sustainability, artificial intelligence and materials. The university is headquartered on its Jurong West campus at 50 Nanyang Avenue, Singapore.

Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a leading college that is known for its excellent curriculum, outstanding and impactful research, and world-renowned faculty.

A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow’. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing.

The QID Lab, led by Asst Prof Du Yuxuan at NTU’s College of Computing and Data Science, works at the intersection of quantum computing and artificial intelligence, spanning quantum machine learning, quantum learning theory and AI for quantum science. The Research Fellow will join a project under Singapore’s AQAS programme, developing advanced AI, including large language models and neural decoders, for quantum error correction.

Key Responsibilities:

  • Develop LLM-driven agentic systems (“AI scientists”) that automatically discover and optimise quantum error-correcting codes, such as quantum LDPC codes, under realistic circuit-level noise and hardware constraints.
  • Design scalable neural decoders, such as Transformer-based foundation decoders, that generalise across code families and distances, and benchmark them against state-of-the-art classical decoders.
  • Investigate AI-assisted synthesis and optimisation of fault-tolerant circuits, including syndrome extraction circuits and decoding for logical operations.
  • Develop low-latency, hardware-efficient decoding methods, such as model compression and FPGA deployment, to support real-time quantum error correction.
  • Build and maintain open-source software and large-scale simulation pipelines on high-performance computing resources.
  • Publish research in leading venues in quantum information and machine learning, and contribute to project reports, deliverables and grant proposals.
  • Lead and mentor a team of PhD, Master’s and undergraduate researchers, and coordinate day-to-day research activities within the lab.
  • Collaborate with academic, industry and hardware partners within the AQAS programme and Singapore’s quantum ecosystem.

Job Requirements:

  • PhD degree in Computer Science, Computer Engineering, Physics, Electronics Engineering or equivalent.
  • Independent, highly analytical, proactive and a team player.
  • Excellent teamwork and verbal, written communication skills.
  • In-depth knowledge relevant to the project domain, including quantum error correction, fault-tolerant quantum computing and decoding algorithms.
  • Demonstrated capability to conduct innovative research, evidenced by first-author publications in leading journals and conferences (e.g., Physical Review Letters, Nature Communications, ICML, NeurIPS, ICLR).
  • The ability and willingness to adapt and incorporate novel ideas and approaches, such as large language models and AI agents, in scientific research.
  • Demonstrated ability to formulate hypothesis and design effective experimental plans.
  • Ability to design and implement new computational and numerical methods.
  • High-level expertise in the required modelling methods, including deep learning (e.g., PyTorch), large language models and circuit-level QEC simulation.
  • Ability to initiate collaboration research in multidisciplinary team.
  • Oversee and report project progress.
  • Ability and willingness to work some flexible hours.
  • Experience running large-scale computational experiments on HPC or GPU clusters.
  • Proven ability to lead a research group, including supervising PhD and Master’s students and undergraduate interns and coordinating multiple concurrent projects.

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU
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