Research Fellow (Deep Learning/Quantum Computing)

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. Today, we are ranked #2 for AI and Computer Science by US News Best Global Universities; and #8 for Data Science and AI by QS World University Ranking.

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.

We are seeking for a Research Fellow for a term of one year to conduct high quality research. The successful candidate will play a pivotal role in a project centered around Large-scale Deep Learning Models (LMs), with a focus on learning theory and security of LMs from a physical perspective.

Key Responsibilities:

• To conduct independent research in large-scale deep learning models.

• To investigate the learnability of LMs from a physical perspective.

• To produce publications in top conferences and journals.

• To offer guidance and assistance to any students involved in the project.

• To collaborate with industrial and academic partners.

• To collaborate with interdisciplinary teams, including experts in physics, deep learning, and application domains.

• To perform any other duties related to the research program.

Job Requirements:

• Preferably PhD in Physics, Computer Science, Machine Learning or relevant fields.

• Strong background in quantum machine learning or physics-based approaches to model learning, enabling the candidate to contribute physical insights into the learning and security of LMs.

• Strong publication record in top conferences/journals, such as PRL, NeurIPS, T-PAMI, TNNLS, and etc.

• Experience in interdisciplinary studies of deep learning and physics is preferred.

• Knowledge of programming skill with deep learning architectures, such as PyTorch, TensorFlow, etc.

• Proficiency of programming skill with quantum machine learning architectures, such as PennyLane, Qiskit, and similar platforms, is preferred.

• Capable of handling multiple tasks across projects and research activities.

• Showing excellent communication skills, and willingness to learn.

• Able to work under limited supervision and excel as an effective team member.

We regret that only shortlisted candidates will be notified.