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corresponding numerical methods in computer codes. Experience with numerical methods for solving partial differential equations such as finite difference, finite element, and/or spectral methods. Ability to
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corresponding numerical methods in computer codes. Experience with numerical methods for solving partial differential equations such as finite difference, finite element, and/or spectral methods. Ability to
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applications, including biology, materials science, and astrophysics, and uses a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data
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physical principles of acoustics and the related numerical modelling techniques, such as the Finite Element Method (FEM), Boundary Element Method (BEM), and/or with the basic principles of Machine
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, Julia, MATLAB, or C++, and with machine-learning frameworks such as PyTorch, JAX, or TensorFlow, is desirable. Previous experience with finite-element, finite-difference, spectral, or iso-geometric
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research experience in mechanics Prior exposure to numerical/computational modelling methods (e.g. discrete element method or finite element analysis) Strong programming skills Good written and verbal
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numerical methods and finite-element modeling using COMSOL · An interest in biological systems and in connecting theoretical models with experimental observations · Enthusiasm, self-motivation
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uses a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics offers excellent
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collaborate with colleagues, researchers, and other university staff. Experience with finite element libraries and numerical methods would further strengthen the application. Additional Information
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; magnetostatic simulations using finite element methods; thermal modelling of heat pump systems using finite element models; and scientific publications in the field of magnetocaloric materials