We are hiring highly motivated and talented Postdoctoral Associates who are interested in advancing the state of the art in resource-efficient machine learning at the Singapore-MIT Alliance for Research & Technology (SMART). This position is part of the program: “Mens, Manus, and Machina: How AI empowers people and the city in Singapore (M3S).” The role offers a 1-year appointment with the possibility of renewal/extension, focusing on establishing a new paradigm for resource-efficient machine learning that balances computational efficiency with state-of-the-art performance.
Research Focus: Foundation Models & Next-Generation Methods
As the field increasingly pivots toward foundation models, efficiency has become a central challenge. Addressing this challenge requires approaches that go beyond incremental optimization. We seek researchers to develop next-generation machine learning methods that fundamentally rethink how large-scale AI systems are trained, fine-tuned, and deployed. Our focus is on the development and application of advanced techniques, including AutoML, Bayesian optimization, neural architecture search, reinforcement learning, and active learning, with the explicit goal of achieving significant gains in computational efficiency without sacrificing performance.
The postdoctoral fellow will be based at the SMART Centre in Singapore. You will be working directly with the following leading faculty from MIT and NUS:
Daniela Rus (MIT) https://danielarus.csail.mit.edu/
Armando Solar-Lezama (MIT) https://people.csail.mit.edu/asolar/
Bryan Kian Hsiang Low (NUS) https://www.comp.nus.edu.sg/~lowkh/index.html
Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.
Sign in to browse authentic reviews, anonymous ratings and salary data before you apply.