Postdoctoral Research Fellow in Data-Efficient Machine Learning
7 days ago
Project Overview
We are hiring postdoctoral fellows to advance the state of the art in data-efficient machine learning at SMART. This new program, Mens, Manus and Machina: How AI empowers people and the city in Singapore (M3S), focuses on applying data-efficient techniques to large language models.
The selected candidates will investigate how concepts like data attribution, data selection/reweighting, data valuation, data curation, Bayesian optimization, and retrieval-augmented generation can be applied in the context of LLMs. They will also examine important issues involving AI privacy, model auditability, and updatability.
Responsibilities- Conduct research on topics related to data-efficient machine learning in the context of LLMs
- Investigate how these concepts can be applied in the context of LLMs
- Develop, implement, and evaluate experiments to characterize the feasibility and performance of proposed research ideas
- Collaborate with other PhD and undergraduate students to publish research results in top-tier conferences and journals
The postdoctoral fellows will be jointly advised by Prof. Daniela Rus, Prof. Alex 'Sandy' Pentland, and Assoc. Prof. Bryan Low, and based at SMART in Singapore.
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