Overview
VinUniversity is currently seeking highly motivated individuals for three academic positions: one postdoctoral role, one Master’s position, and one Ph.D. opportunity. These roles are centered around the fields of machine learning, multimodal learning, and autonomous systems, with a particular emphasis on safe and secure machine learning methodologies.
Background & Relevance
The significance of safe machine learning has gained increasing attention as AI systems become more integrated into various sectors. Research in this area aims to ensure that machine learning algorithms are not only effective but also secure and reliable. With applications spanning sustainability, healthcare, and material discovery, the development of robust algorithms is crucial for advancing technology in a responsible manner.
Key Details
- Positions Available: 1 Postdoctoral, 1 Master’s, 1 Ph.D.
- Research Focus: Safe and secure machine learning, including Large Language Models (LLMs) and Vision-Language Models.
- Topics of Interest: Pre-training strategies, fine-tuning techniques, bias and fairness, interpretability, adversarial robustness, and alignment in AI systems.
- Potential Applications: Sustainability, farming, material discovery, healthcare.
- Advisors: Khoa Doan (Assistant Professor, CECS) and Nitesh Chawla (Honorary Professor at VinUniversity, Frank M. Freimann Professor at the University of Notre Dame).
- Collaboration Opportunities: Candidates may collaborate with international partners, including the University of Notre Dame, UIUC, the University of Stuttgart, and MPI.
- Funding: Strong candidates may receive funding to spend time at the University of Notre Dame.
Eligibility & Participation
These positions are open to candidates who are passionate about advancing the field of machine learning. The ideal applicants should possess a strong background in relevant areas and demonstrate a commitment to research excellence.
Submission or Application Guidelines
Interested candidates are encouraged to submit their CV along with recent publications to Dr. Khoa D Doan at khoa.dd@vinuni.edu.vn. This is an excellent opportunity for those looking to contribute to cutting-edge research in safe machine learning.
More Information
The focus on safe and secure machine learning is vital as AI technologies continue to evolve. By addressing challenges such as bias, interpretability, and adversarial attacks, researchers can help ensure that AI systems are not only powerful but also ethical and trustworthy. This initiative at VinUniversity aligns with global efforts to promote responsible AI development.
Conclusion
This is a remarkable opportunity for aspiring researchers to engage in significant work at the intersection of machine learning and safety. Interested individuals are encouraged to apply and contribute to this important field of study.
Category: PhD & Postdoc Positions
Tags: machine learning, multimodal learning, autonomous systems, large language models, vision-language models, adversarial robustness, bias and fairness, interpretability, sustainability, healthcare, VinUniversity, Nitesh Chawla, Khoa Doan
