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structures i.e. in aircrafts, containing adhesive and disband damages. The research activities will initially include one or more of the following areas: Advanced finite element modelling of disband damaged
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of developing novel computational frameworks that seamlessly integrate machine learning techniques with established methods in computational mechanics, such as the Phase-field Finite Element Methods. Potential
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element method, wave propagation analysis, inverse problem, machine learning (ML), and artificial neural network. Strong background in research publications in the desired field. Experience mentoring other
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and knowledgeable in the areas of stress analysis (including the Finite Element Method), material characterisation (particularly flow stress determination and modelling), mechanical testing methods
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by using commercial software such as Ansys, Abaqus, SolidWorks, etc. Experience in computational fluid dynamics (CFD) modelling or finite element (FE) modelling; Fundamental knowledge in fluid
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Application/Interview Strong background in semiconductor device design and/or simulation, including photolithographic mask layout Essential Application/Interview Experience of 3D finite element modelling (FEM
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with practical finite element analysis using ANSYS Workbench Excellent written and oral skills and proficient with MS Office and MS Excel. Preferred Knowledge, Skills, and Abilities: An MS degree
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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Principal Investigator (PI) or Co-Principal Investigator (Co-PI) on research studies. Perform non-linear, dynamic, finite element analysis (FEA) and design for various research studies involving low- to high
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(PDEs). Our goal is to design finite-dimensional controllers that are not only straightforward to implement but also robust against real-world imperfections, including system disturbances, measurement