The Wallenberg-NTU Postdoctoral Fellowship is to bring outstanding young researchers, who have graduated from a Swedish university, to NTU for two years of postdoctoral research and studies. The Postdoctoral Fellows are given the opportunity to participate in a broad range of interdisciplinary activities and programs that characterize NTU’s approach to research and education.

Key Responsibilities:

The fellow in this research project is required to:

• Develop and implement decoupled AI-based surrogate models for reliability-based topology optimization

• Develop geometry-generalizing machine learning models

• Implement explainability-driven active learning strategies for RBTO problems

• Perform finite element simulations to be used within AI-based surrogate frameworks

• Validate developed methods using benchmark engineering case study problems

• Prepare technical reports, research publications, and documentation of developed methods

• Present research findings at internal meetings, conferences, and workshops

• Collaborate and assist with the supervision of undergraduate and postgraduate students on projects

Job Requirements:

• A PhD in Mechanical Engineering, Civil Engineering, Computational Engineering, or a related field

• Strong background in reliability engineering, uncertainty quantification, and optimization methods

• Experience with surrogate modeling, machine learning, or AI in engineering applications

• Proficiency in programming (Python, MATLAB, or C++)

• Experience with numerical simulation methods (e.g., finite element analysis)

• Familiarity with active learning and explainable AI techniques

• Strong mathematical skills in probability and statistics

• Ability to design and validate computational models for complex engineering systems

• Excellent academic writing and communication skills

• Ability to work independently and collaboratively in interdisciplinary research environments

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU