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Field
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modelling activity. Demonstrated expertise in finite-element methods or related numerical techniques. Experience in code development, HPC architectures, and parallel programming is highly desirable
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About the role As a postdoctoral research fellow, you will participate in an industry-funded project and perform numerical studies, develop tools facilitating the interaction of finite element
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classification. The work will involve analytical studies, computer simulations, and finite element (FE) analysis, alongside experimental development and validation. Entry requirements The minimum entry requirement
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biology / bioinformatics / genomics, or 2. Computer Aided Engineering (CAE) for mechanical/aerospace applications (finite element analysis, finite difference methods, Lattice Boltzmann methods, or other
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CAD tools Finite-element analysis and simulation Rapid prototyping and additive manufacturing Signal processing and data analytics, control systems Machine learning or computer vision Product
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structure-preserving methods for mathematical models of physical systems, including topics such as geometric numerical integration, finite-volume and finite-element methods, variational formulations
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control Motion-control systems, stepper motors, encoders, and automation equipment Mechanical design using CAD tools Finite-element analysis and simulation Rapid prototyping and additive manufacturing
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
. Basic knowledge of the mechanical behaviour of composite materials. Experience with the finite element method for structural analysis. Experience in the characterisation and modelling of composite
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languages; solid background in aerospace structures, structural mechanics and in numerical methods for structural analysis; study, research, or thesis experience in finite element modeling (FEM), thermo
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Tata Institute of Fundamental Research | Karnataka Health Institute, Karnataka | India | about 2 months ago
, stochastic analysis, inverse problems, computational PDE, finite element method, numerical linear algebra and optimization, machine learning and data science, and mathematical and computational biology.