Research Fellow/Senior Research Fellow (AGI Research)
NATIONAL UNIVERSITY OF SINGAPORE
Singapore, Singapore
Not specified
Ph.d. in computer science or related field
Proficiency in pytorch, tensorflow, and jax
Demonstrated expertise in agi research
The National University of Singapore is seeking a Research Fellow or Senior Research Fellow to join their Learning and Vision Lab, focusing on advancing research in Artificial General Intelligence (AGI) and Robotics. The ideal candidate will have a strong academic background, including a Ph.D. and significant publication record in top-tier AI conferences and journals, along with proficiency in relevant programming frameworks
Job Summary
The position offers a unique opportunity to develop novel computational architectures for foundation models and pioneer self-improving methodologies.
Candidates will lead groundbreaking research in AGI with a focus on efficient and evolving systems as well as embodied AI robotics.
Applicants must collaborate with an interdisciplinary team to produce influential publications in premier conferences and journals.
Matching Summary
Match Score: 85
The National University of Singapore is seeking a Research Fellow or Senior Research Fellow to join their Learning and Vision Lab, focusing on advancing research in Artificial General Intelligence (AGI) and Robotics. The ideal candidate will have a strong academic background, including a Ph.D. and significant publication record in top-tier AI conferences and journals, along with proficiency in relevant programming frameworks.
Skills & Requirements
Must-have
Ph.D. in Computer Science or related field
Proficiency in PyTorch, TensorFlow, and JAX
Demonstrated expertise in AGI research
Nice-to-have
Multiple papers with 100+ citations
Best paper awards at leading conferences
Strong record in international academic competitions
Key Requirements
Ph.D. in Computer Science, Statistics, Applied Mathematics, Data Science, or related fields
First author publication record in top AI conferences or high-impact journals