Wallenberg- NTU Postdoctoral Fellow
ExternalFull-timeOn-siteToday
DocumentationMachine LearningMATLABPython
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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++)
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Company Intel
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