Finite-element modelling of thermo-mechanical processes
Experience with data-driven modelling or machine learning
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A*STAR Research Entities is seeking a motivated Scientist for its Advanced Manufacturing & Semiconductor Division to contribute to research in physics-based modeling and machine learning for semiconductor packaging reliability. Ideal candidates should possess a PhD in relevant fields and experience in numerical simulations, particularly finite-element modeling, as well as programming skills in Python or MATLAB.
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Job Summary
The role involves integrating finite-element simulations and physics-based models with machine learning approaches for predictive reliability analysis.
Candidates will develop data-driven surrogate models and reduced-order models specifically for thermo-mechanical behaviour in electronic packaging structures.
The position offers opportunities to collaborate with interdisciplinary teams and industrial partners within the semiconductor ecosystem.
Matching Summary
Match Score: 75
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A*STAR Research Entities is seeking a motivated Scientist for its Advanced Manufacturing & Semiconductor Division to contribute to research in physics-based modeling and machine learning for semiconductor packaging reliability. Ideal candidates should possess a PhD in relevant fields and experience in numerical simulations, particularly finite-element modeling, as well as programming skills in Python or MATLAB.
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Skills & Requirements
Must-have
PhD in Mechanical Engineering or related field
Finite-element modelling of thermo-mechanical processes
Experience with data-driven modelling or machine learning
Strong programming skills in Python, MATLAB, or FORTRAN
Nice-to-have
Experience with ABAQUS, ANSYS, or COMSOL simulation tools
Background in high-performance computing or large-scale simulations
Passion for advancing AI-driven modelling technologies