Singapore – Fully Funded PhD in Safe and Robust AI at Nanyang Technological University - PhDFinder

Description

This position is no longer available.

University: Nanyang Technological University

Country: Singapore

Deadline: Not specified

Fields: Computer Science, Artificial Intelligence, Mathematics, Statistics, Data Science

Are you passionate about advancing the safety and reliability of artificial intelligence, and eager to contribute to foundational research with real-world impact? If your academic ambitions revolve around creating trustworthy AI systems and shaping the future of technology, a fully funded PhD opportunity at Nanyang Technological University (NTU) in Singapore could be the ideal next step in your career.

Strong, reliable, and interpretable AI systems are increasingly critical as artificial intelligence becomes embedded in safety-critical applications across industries. At NTU, you will have the chance to work at the cutting edge of AI safety and robustness, developing methodologies with precise correctness guarantees and minimal assumptions, and contributing to the theoretical and practical advancements of the field.

About The University Or Research Institute

Nanyang Technological University (NTU) is one of Asia's leading research-intensive universities, consistently ranked among the top universities globally. Located in Singapore, NTU boasts a vibrant and diverse faculty, fostering a dynamic academic environment that is both collaborative and innovative. The university is extremely well-resourced, particularly in terms of computing infrastructure, making it an excellent place for ambitious researchers in artificial intelligence and related fields. NTU's commitment to excellence in research and education is evident in its strong support for both local and international students, and its strategic location in Singapore offers access to a thriving tech ecosystem and global research networks.

Research Topic and Significance

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The Central Focus Of This PhD Opportunity Is On Safe And Robust AI Systems. As Artificial Intelligence Increasingly Powers Critical Infrastructure, Healthcare, Finance, And Autonomous Systems, Ensuring The Reliability And Safety Of These Technologies Has Never Been More Important. The Research Addresses Key Challenges In

– Generative modelling

– Geometric deep learning

– Causal inference

– Uncertainty quantification

The group's work involves developing new methodologies that come with precise correctness guarantees under minimal assumptions, which is crucial for deploying AI in high-stakes environments. Additionally, the lab explores advanced tools for describing and reasoning about AI systems, leveraging concepts from category theory, programming languages theory, and proof assistants. This foundational research has significant implications for how AI is designed, verified, and trusted in society.

Project Details

The positions are available in the group led by Dr. Rob Cornish, who is actively recruiting PhD students, postdocs, and research assistants. The lab tackles a range of topics within AI safety and robustness, with a strong emphasis on rigorous methodology and scalability to real-world, safety-critical applications. In addition to research in generative modelling, geometric deep learning, causal inference, and uncertainty quantification, the group develops innovative tools for formal reasoning about AI systems.

The positions come with full scholarships, covering tuition and a stipend for four years, and are open to both local and international students. The lab is well-supported by NTU's extensive computing resources, providing an excellent environment for cutting-edge AI research.

Candidate Profile

The ideal candidates for these positions are talented and ambitious individuals with a strong background in mathematics, statistics, and/or computer science. The group welcomes applicants who are intellectually curious, passionate about AI safety and reliability, and eager to engage with foundational and applied research. While having a clear research plan is beneficial, it is not a strict requirement—motivated candidates with a demonstrated interest in the field and a desire to contribute to the advancement of AI safety are encouraged to apply.

Application Process

To apply for these fully funded PhD positions, interested candidates should prepare the following materials:

– A short (1-2 paragraph) introduction about yourself

– Your CV

– Your academic transcripts

– Your favourite piece of technical writing that you produced as lead author (e.g., undergraduate thesis, paper, or report)

Intakes occur in January and August each year. To ensure timely processing, prospective applicants are encouraged to get in touch as soon as possible before their desired start date. There is no specified deadline, but early contact is recommended to allow sufficient time for the application process.

All enquiries and applications should be sent to Dr. Rob Cornish at:

rob[dot]cornish[dot]ntu[dot]recruiting[at]gmail[dot]com

For more information and details on how to apply, please visit:

Conclusion

This is a unique opportunity to join a world-class research group at NTU and contribute to the development of safe, robust, and trustworthy AI systems. If you are motivated to make a meaningful impact in artificial intelligence and have the necessary background, you are strongly encouraged to apply. For more opportunities like this, follow updates and explore similar positions to advance your academic and professional journey.

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