job description
Join Nanyang Technological University (NTU), a globally renowned research institution, as a Research Fellow in AI-Driven Transportation Engineering and pioneer the future of road safety analytics. This fully remote position, based in Bali, Indonesia, offers the perfect blend of cutting-edge research and tropical work-life balance in locations like Canggu, Ubud, or Kuta.
As a key member of our Smart Mobility Research Lab, you will leverage artificial intelligence, machine learning, and big data analytics to develop innovative solutions for transportation safety. Your work will directly impact global road infrastructure, reducing accidents through predictive modeling and real-time traffic analysis. This role is ideal for visionary engineers passionate about autonomous vehicles, smart cities, and sustainable urban planning.
NTU provides a collaborative environment with access to high-performance computing resources, global research networks, and industry partnerships. You’ll work alongside leading experts in transportation engineering while enjoying the flexibility of remote work in Bali’s vibrant tech community. Whether you’re analyzing traffic patterns in Denpasar or developing AI models in Ubud, this role offers both professional growth and an unparalleled lifestyle.
If you’re a forward-thinking researcher with expertise in AI, transportation systems, or data science, we invite you to shape the future of mobility with us. Apply now and be part of a team that’s redefining road safety through technology.
Responsibility
- Design and develop AI-driven models for real-time road safety analytics and accident prediction.
- Lead research projects focused on autonomous vehicle integration, traffic flow optimization, and smart infrastructure.
- Collaborate with cross-functional teams to implement machine learning algorithms for transportation data analysis.
- Publish findings in high-impact journals and present at international conferences.
- Develop predictive maintenance systems for road networks using IoT and sensor data.
- Mentor junior researchers and contribute to grant proposals for funding opportunities.
- Work with government and industry partners to translate research into real-world applications.
- Stay updated on emerging trends in AI, transportation engineering, and smart city technologies.
Qualifications
- PhD in Transportation Engineering, Civil Engineering, Computer Science, or a related field.
- Proven experience in AI/ML applications for transportation systems (e.g., traffic prediction, accident analysis).
- Proficiency in Python, R, or MATLAB for data analysis and modeling.
- Strong background in statistical analysis, deep learning, or reinforcement learning.
- Experience with big data tools (e.g., Hadoop, Spark, TensorFlow, PyTorch).
- Publications in peer-reviewed journals or conferences related to transportation or AI.
- Excellent communication skills for collaborating with global teams and stakeholders.
- Ability to work independently in a remote research environment.