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Field
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. Particular emphasis will be placed on characterizing defect populations and incorporating this information into finite element models, either through direct reconstruction of microstructures or statistically
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placed on characterizing defect populations and incorporating this information into finite element models, either through direct reconstruction of microstructures or statistically generated synthetic
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testing Perform numerical modelling and simulation, such as finite element modelling, parametric studies, and calibration against test data. Analyse experimental and numerical results, and prepare technical
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) professional or academic experience in Machine Learning or finite element modelling. 5. Formalization of the applications: Applications are formalized through a request addressed to the Rector of Universidade do
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Technology. Additional Actions : Composite Materials, Finite Element Modelling (FEM), Impact Engineering, High-Rate Experimental Mechanics, AI Assisted Surrogate Modelling
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structural modelling and analysis tools (e.g., finite element modelling, structural simulation) is desirable. Good interpersonal, written and verbal communication skills, with the ability to work independently
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, suitable for deployment on ARSPECTRA devices. You will work at the interface between finite-element modelling, software engineering and embedded/edge computing. Key Responasbilities: Develop and optimise
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that the master's degree has been awarded. Programming skills, e.g., Fortran or C++, is a requirement. Competence in the theory of the finite element method is an advantage. Competence in the theory
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finite element analysis, finite difference schemes, or Monte Carlo simulations. Mentoring Assist in mentoring graduate and undergraduate students in related projects. Collaborate with faculty and students
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mechanics and analysis Experience with the following: Structural health monitoring (SHM) Finite element modeling (e.g., ABAQUS, SAP2000, ANSYS) Machine learning / AI (Python, TensorFlow, PyTorch) Demonstrated