VinUni Pathways to PhD Programs

(VinUni-3P)

Materials – Energy – Environment

Program Overview:

The VinUni Pathways to PhD Programs (VinUni-3P) is a groundbreaking initiative designed to address a critical gap in Vietnam’s higher education and research ecosystem. In most universities, Bachelor’s degree (BS) graduates are not financially supported or institutionally guided to continue research or pursue higher education programs at their alma mater. As a result, many promising students abandon research careers altogether, driven by financial necessity or lack of mentorship. This leads to a significant loss of research potential and scientific innovation.

Program Mission:

VinUni-3P aims to bridge this gap by providing research scholarships and hands-on mentorship to talented BS and MS graduates with a strong interest in materials research. The program offers these students a unique opportunity to:

• Continue and deepen their research after graduation
• Participate in cutting-edge projects at VinUni’s World-Class Research Centers
• Be trained on state-of-the-art equipment and techniques
• Develop an internationally competitive research portfolio

Research Experience and Mentorship:

Participants will be fully immersed in active research environments at VinUni. They will:

• Work closely with postdoctoral researchers and Principal Investigators (PIs)
• Join dynamic research teams in fields aligned with their interests
• Gain experience in:
  • Research design and experimentation
  • Data collection, analysis, and interpretation
  • Academic writing and publishing in ISI-indexed journals
  • Scientific communication at meetings and conferences

This experience will prepare students not only for PhD applications but also to contribute meaningfully to the global research community.

PhD Opportunities:

Qualified and high-performing participants will be considered for fully funded PhD scholarships to:

• VinUni’s own excellent PhD programs
• Joint PhD programs between VinUni and top-ranked global institutions, including Cornell University, NTU, Cambridge University, etc.

How to Apply:

Interested candidates should submit their CV and reference letters (2) to: [email protected]

Applications are reviewed on a rolling basis, and candidates will be notified of the decision within one week.

Who Should Apply:

• Recent BS graduates from any university in Vietnam who are considering a MS or PhD
• Master’s students preparing to transition into a doctoral program
• Candidates with a strong academic background and a demonstrated interest in research

Why VinUni-3P?:

• Access to globally recognized research centers and facilities
• Mentorship by international-caliber scientists
• Supportive environment to develop your full potential as a researcher and a leader
• Direct pathway into top-tier PhD programs in Vietnam and abroad

List of Projects:

1. Agentic AI for Personalized Recommendation: Toward Autonomous and Explainable Recommender Systems

This project develops next-generation intelligent recommendation systems based on Agentic AI that understand user needs, learn from feedback, and provide transparent explanations. By integrating large language models with reasoning, planning, and self-improvement, it enables adaptive and explainable personalization beyond black-box systems. Applications span education, healthcare, and sustainable e-commerce, advancing ethical, human-centered AI with greater trust, efficiency, and fairness.

2. BioDroneX: AI-Enhanced Bio-Inspired Drone for Adaptive Multi-Environment Missions

BioDroneX is an AI-enhanced, bio-inspired drone with computer vision, designed to operate across air, land, and water using adaptive structures, advanced materials, and intelligent navigation. It enables safe access to hazardous or hard-to-reach areas for disaster response, environmental monitoring, smart agriculture, and industrial inspection. By combining biological principles, AI, and advanced 3D printing, the project aims to create autonomous cross-domain drones that reduce human risk and enhance societal resilience.

3. Adaptive Reinforcement Learning for Traffic Control

Urban traffic faces rising congestion, delays, and emissions, while existing adaptive control solutions often struggle with real-world complexity. This research seeks to develop a control policy using advanced adaptive algorithms and hierarchical multi-agent reinforcement learning to handle dynamic, large-scale traffic networks. The work supports Smart City goals by reducing congestion and emissions and enhancing mobility.

4. On-Device Small Language Models for Private Edge AI

Builds privacy-preserving and efficient small LMs with agentic reasoning, enabling secure AI use in sensitive domains such as health, finance, and education.

5. GenPhys-DTs: Generative Physical AI and Digital Twins

The projects develops a generative AI framework integrated with physics simulations for biomedical, manufacturing, and infrastructure applications, enabling adaptive and cross-domain digital twins.