Postdoctoral Fellowship in Robot Learning and Uncertainty Quantification at NTU

Date:

Overview

This is an exciting opportunity for a postdoctoral fellowship at Nanyang Technological University (NTU) in Singapore, focusing on the innovative fields of Robot Learning and Epistemic Uncertainty Quantification. The fellowship is designed for candidates who are eager to engage in research that bridges robotics with statistical machine learning, under the guidance of Assistant Professor Yoonchang Sung and Dr. Siu Lun Chau.

Background & Relevance

The intersection of robotics and machine learning is a rapidly evolving area that holds significant promise for advancing technology. As robots become increasingly integrated into various sectors, understanding and quantifying uncertainty in their learning processes is crucial. This research area not only enhances the performance of robotic systems but also contributes to the foundational methodologies that support their development.

Key Details

  • Fellowship Program: NTU AI-for-X Postdoctoral Fellowship Program
  • Research Focus: Robot Learning and Epistemic Uncertainty Quantification
  • Location: Nanyang Technological University, Singapore
  • Application Link: Apply Here

Eligibility & Participation

This fellowship is targeted at candidates with a robust background in machine learning, robotics, or related fields. Ideal applicants should possess a strong motivation to contribute to the research themes outlined in the fellowship program.

Submission or Application Guidelines

To apply for the fellowship, candidates should follow these steps:
1. Review the details of the fellowship program and proposed research thrusts.
2. Prepare your application materials, highlighting your relevant experience and motivation.
3. Submit your application through the provided link: Application Form.

Additional Context / Real-World Relevance

The research conducted in this fellowship will not only contribute to academic knowledge but also have practical implications in the development of intelligent robotic systems. As industries increasingly rely on automation, understanding how robots can learn from and adapt to uncertain environments is vital for their successful deployment in real-world applications.

Conclusion

This postdoctoral fellowship presents a unique opportunity for researchers interested in the dynamic fields of robotics and machine learning. Interested candidates are encouraged to apply and contribute to this cutting-edge research area. For further inquiries, please reach out to Dr. Siu Lun Chau at siulun.chau@ntu.edu.sg.


Category: PhD & Postdoc Positions
Tags: robotics, machine learning, epistemic uncertainty, statistical machine learning, ntu, postdoctoral fellowship, cross-disciplinary research

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