Research Assistant (Physics/Computer Science/Engineering/Mathematics/Machine Learning)

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.

Key Responsibilities:

• To conduct independent research in quantum algorithm design.

• To seek and demonstrate practical utility of using AI for automating quantum algorithm design.

• To analyze complex wave-based physical systems and their high-dimensional parameter spaces in the context of quantum algorithm design.

• 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, chemistry, and those who work on quantum computing hardware.

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

Job Requirements:

• Preferably Bachelor’s degree in Physics, Computer Science, Engineering, Mathematics, Machine Learning or relevant fields.

• Experience in interdisciplinary research involving physics, deep learning, and mathematics is preferred.

• Strong theoretical background in physics, quantum many-body physics, quantum algorithms, or closely related areas in complex physical systems (e.g., optics, photonics, or wave-based systems).

• Good programming skills in Python. Familiarity with scientific computing frameworks (e.g., PyTorch, TensorFlow, or quantum computing toolkits such as Qiskit or PennyLane) will be an advantage.

• Experience in quantitative modelling, optimization methods, or the analysis of complex physical systems is preferred.

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

• Show excellent communication skills, and willingness to learn.

• Able to excel as an effective team member.

We regret that only shortlisted candidates will be notified.