About this role
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.
Also in Data Science