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of materials The work will entail: This PREP position focuses on developing traceable standards for 5G, 6G, and beyond. The position requires finite element simulations, programming, network analysis
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: This PREP position focuses on developing traceable on-wafer standards for 5G, 6G, and beyond. The position requires finite element simulations, programming, network analysis, dimensional metrology, web-based
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acquisition, instrumentation and monitoring during laboratory testing Perform numerical modelling and simulation, such as finite element modelling, parametric studies, and calibration against test data. Analyse
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Requirements PhD/Master’s in Naval Architecture, Ocean Engineering, Civil Engineering, or related field. Proficiency in hydrodynamic modeling tools (e.g., WAMIT, ANSYS AQWA, OrcaFlex) and finite element analysis
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-destructive testing (NDT) techniques for structural materials is desirable. Experience with structural modelling and analysis tools (e.g., finite element modelling, structural simulation) is desirable. Good
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. This includes conducting finite element modeling, ship resistance and stability assessments, as well as overseeing AM process and reporting. The role also involves designing and validating connectors
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with morphological image data is essential. Experience in geometric morphometrics and/or finite element analysis is desirable. Customer advert reference: B02-10342
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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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. This includes conducting finite element modeling, ship resistance and stability assessments, as well as overseeing AM process and reporting. The role also involves designing and validating connectors
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
optimized design approaches. Run high-fidelity micromechanical simulations (finite element) to obtain the homogenised properties of a composite (ply-level) Use Convolutional Neural Networks (CNNs) to obtain