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models (e.g., finite element analysis) to complement and contextualize experimental findings. Apply CAD tools such as ANSYS and SolidWorks to produce geometric models for experimental specimens
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for Partial Differential Equations with emphasis on standard and non standard finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further
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, cryogenics, finite-element simulations (FEM), and data acquisition systems is desirable Excellent written and spoken English skills Strong teamwork and communication skills in interdisciplinary research
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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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Partial Differential Equations with emphasis on standard and non standard finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further
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ability to collaborate with field-based glaciologists and seismologists. • FEM Tools: Strong skills in the finite element method. Practical experience with Elmer/Ice and/or GlaDS is a plus. • Data
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supercomputers (in terms of achievable parallelism) for quadratic unconstrained binary optimization. Another example could be stochastic spiking neurons for solving finite-element tessellations in a
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, computational modeling, finite element analysis, computational geometry, fluid mechanics, scientific visualization, HPC and distributed computing. Substantial experience in programming (i.e., fluent in