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.

Wallenberg- NTU Postdoctoral Fellow