PhD Student
3 months ago
Tasks:
Trustworthy Machine Learning (ML) is an emerging field dedicated to ensuring that ML systems operate in a reliable, fair, and transparent manner. As ML applications become increasingly integrated into critical sectors such as mobility, manufacturing, and autonomous systems, the importance of trustworthiness in these systems has never been more paramount.
This position offers an exciting opportunity to conduct cutting-edge research in developing and ensuring trustworthiness in ML systems.
The successful candidate will be working at world-class laboratories in NUS and Bosch, contribute to advancing the field by addressing key challenges such as transparency, fairness, accountability, robustness, and privacy in ML models and applications.
Qualifications
Singaporean or PR (to be eligible for EDB-IPP program). Bachelor's or Master's degree in Computer Science, Electrical or Electronics Engineering Fulfill the National University of Singapore (NTU/NUS) PhD programme requirements. Excellent written and verbal communication skills. Curious, self-motivated, able to work independently, and a passion to tackle real-world problems through research. Relevant research experience in the field of machine learning, artificial intelligence, and data science. Familiarity with concepts of fairness, accountability, transparency, and ethics in AI/ML is a plus. Strong academic record, with at least one publication in top-tier conferences or peer-reviewed journals (preferred). Fresh degree holders with excellent academic results are also encouraged to apply.
Additional Information
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