PhD program in CS at NUS
We are always looking for PhD students, postdocs, and visiting students to join our lab in the Department of Computer Science (CS) or the Institute of Data Science (IDS) at the National University of Singapore (NUS).
If you are interested in joining our lab, please contact me at kenji at comp.nus.edu.sg
- Name: Kenji Kawaguchi
- Education: MIT / Harvard University
- Position: Presidential Young Professor
- Publications: Google Scholar
- Profile: homepage
- Research interests in our lab at NUS: Large Language Models (LLMs) and Deep Learning
Current students at NUS: If you are interested in working with me (with or without joining my lab), please contact me at kenji at comp.nus.edu.sg
Prospective students: If you are interested in joining our lab, please apply directly to the Department of Computer Science or the Institute of Data Science at NUS. If you have questions about joining our lab, please email to kenji at comp.nus.edu.sg
We have fully-funded positions for PhD students. The school will provide fully-paid scholarships with monthly stipend and full tuition fee subsidy for the PhD students under my supervision. The monthly stipend rate will be determined by the school and are subject to change.
NUS School of Computing: Admission Requirements / Application Information
NUS Institute of Data Science: Admission Requirements / Application Information
We have fully-funded postdoctoral positions.
If you would like to work with us, please send your CV and research interests to: kenji at comp.nus.edu.sg
We have different projects available, but the topic is flexible and the candidate can propose a topic of their own interest if they want to.
If you are interested in doing a long term or short term internship please contact kenji at comp.nus.edu.sg
Minimum requirements: bachelor's degree
Preferred qualification: master's degree or PhD
If you are interested in visiting my lab, please feel free to email me.
ABOUT OUR LAB
We have sufficient computational resources to conduct research. We are constantly updating the computational resources. Our lab has access to private two DGX servers with 16 A100 GPUs, one cluster with 8 L40S GPUs, 12 GPU serviers with 96 A4000 GPUs, and NSCC with more than 50 A100 GPUs. We also use Google Cloud Credits on top of these.
We can also purchase your own GPU workstation if needed. Before (as well as after) joining our lab, you can negotiate to purchase your own GPU workstation. NUS and NUS CS have shared GPU clusters, but it is convenient to have your own GPU workstation depending on your research style. We will try our best to avoid the situation where the computational resource is the bottleneck of our research, by accommodating the needs for computational resources as much as possible.
Publications
Our lab will aim to publish impactful works in top conferences in deep learning (NeurIPS, ICLR, ICML, CVPR, AAAI, etc,) as well as top journals in computational physics and applied mathematics. Funding will be available for travel to conferences.
Collaborations
To advance deep learning and the understanding of intelligence, our lab collaborates with researches at MIT, Harvard University, Brown University, Stanford University, Google, and other top institutes around the world.
Co-advising option
I am open to co-advising PhD students at NUS.
Lab members can also expect...
Flexibility in choosing research themes and topics.
Assistance with obtaining internships, postdoc positions and faculty positions.
ABOUT NUS CS
- CS Asia Ranking: 1st (QS World University Rankings 2021), 1st (THE World University Rankings 2021)
- CS World Ranking: 4th (QS World University Rankings 2021), 8th (THE World University Rankings 2021), 8th (US News and World Reports)
- University Asia Ranking: 1st (QS World University Rankings 2021)
- University World Ranking: 11th (QS World University Rankings 2021)