Research fellow

3 days ago


Singapore NTU Full time

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 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 hotbed 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 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:
Conduct independent research in large-scale deep learning models.
Investigate the learnability of LMs from a physical perspective.
Produce publications in top conferences and journals.
Offer guidance and assistance to any students involved in the project.
Collaborate with industrial and academic partners.
Work with interdisciplinary teams, including experts in physics, deep learning, and application domains.
Perform any other duties related to the research program.
Job Requirements:
Preferably a Ph D 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, Neur IPS, T-PAMI, TNNLS, etc.
Experience in interdisciplinary studies of deep learning and physics is preferred.
Knowledge of programming skills with deep learning architectures, such as Py Torch, Tensor Flow, etc.
Proficiency in programming skills with quantum machine learning architectures, such as Penny Lane, Qiskit, and similar platforms, is preferred.
Capable of handling multiple tasks across projects and research activities.
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.
Hiring Institution: NTU
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