- 50 NANYANG AVENUE West Region (Singapore) Singapore

工作地点
职位描述
岗位职责
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:
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.
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