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., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration and haptics feedback in
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, anisotropic conductive film bonding and wire bonding Finite element Method (FEM) simulations (MEMS, Electro-static and Quasi-static simulations) Discrete electronic design (Analog and digital design using COTS
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Education & Experience: PhD Must be competent to model rail buckling, rail fracture, and failure of track structure due to moisture sorption using advanced finite element methods. Also, must be competent
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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, computer science, or a closely related field. Coding experience for the computational modeling of physical and/or engineered systems, preferably with finite-element methods, is a must. Strong programming
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characterization, mechanical testing, 3D microstructural analysis, finite element simulations, atomistic modeling, and thermal transport measurement techniques to advance mechanistic understanding and predictive
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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record in theoretical and/or computational mechanics Knowledge, Skills, and Abilities Excellent analytical and mathematical skills Proficiency in numerical analysis using finite element method (FEM
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team