Quantum AI Research Fellow: Lead QEC & LLM Lab

Nanyang Technological University; Singapore; Sur place; SGD 70 000 - 110 000; Plein temps

Résumé du poste

NTU Singapore’s College of Computing and Data Science invites applications for a Research Fellow to advance LLM-driven systems for quantum error correction and scalable neural decoders.

You will lead a multidisciplinary team, develop AI-assisted quantum technologies, and collaborate with AQAS partners while publishing in top venues. The role leverages HPC resources and requires a PhD and strong research output.

Qualifications

• PhD in Computer Science, Physics, Engineering or equivalent.
• Strong track record of innovative research with first-author publications in leading venues.

Responsabilités

• Develop LLM-driven agentic systems that discover and optimise quantum error-correcting codes.
• Design scalable neural decoders that generalise across code families and benchmark against classical decoders.
• Investigate AI-assisted synthesis and optimisation of fault-tolerant circuits.
• Develop low-latency, hardware-efficient decoding methods and FPGA deployment.
• Build and maintain open-source software and large-scale simulation pipelines on HPC resources.
• Publish research in leading venues and contribute to project reports and grant proposals.
• Lead and mentor PhD, Master’s and undergraduate researchers; coordinate day-to-day lab activities.
• Collaborate with academic, industry and hardware partners within the AQAS programme.

Connaissances

Deep learning

Transformer models

Team leadership

Analytical thinking

Independent researcher

Formation

PhD in CS/Physics/Engineering

Outils

PyTorch

FPGA

Description du poste

NTU Singapore’s College of Computing and Data Science invites applications for a Research Fellow to advance LLM-driven systems for quantum error correction and scalable neural decoders.

You will lead a multidisciplinary team, develop AI-assisted quantum technologies, and collaborate with AQAS partners while publishing in top venues. The role leverages HPC resources and requires a PhD and strong research output.