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finite element methods (FEM) and deep learning approaches. Differentiable FEM enables direct access to sensitivity information within non-linear and coupled systems, while neural networks can be used
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planning, research, and analysis skills, working well under supervision when necessary. The project sits at the intersections of design, manufacturing, composite materials and finite element modelling
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of developing of energy autonomous neural interfaces. The researcher will be in charge of the finite elements simulations to predict and design novel materials and device designs for energy harvesting based
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emphasis on standard and non standard finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further information about our research area and about
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optical components. The design will be done using advanced numerical calculation methods, such as Finite Element Method (FEM) and Finite Difference Time Domain (FDTD) method. Approaches based on inverse
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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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integrity and lifetime of fusion blanket materials. Where to apply Website https://www.swansea.ac.uk/postgraduate/scholarships/research/mechanical-enginee… Requirements Research FieldEngineering
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the use of mathematical software such as MATLAB or Python and CAE software (finite element modeling e.g. COMSOL). Experience with MEMS design and/or microfabrication knowledge are an asset. You have
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consists of a large group of European defense companies and research institutes. The research tasks at UGent-MMS involve several aspects: (i) design and finite element simulation of different propeller
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of computer vision and modelling for biomedical applications. This project focuses on developing finite element models and AI-driven solutions to improve perforator mapping through dynamic infrared thermography