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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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should have for this project, in addition to our standard entry requirements . Essential Criteria BEng/BSc/MSc in Mechanical Engineering, Applied Mathematics, Applied Mechanics, or related discipline such
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://www.chalmers.se/math/ At the division of Applied Mathematics and Statistics we conduct research within probability theory and its applications, the theory and implementation of finite element methods, inverse wave
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for simulations, we aim to explore solution strategies to calculate the amount of water given meteorological data and map data. Here, in addition to traditional discretization methods such as finite elements and
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(variational multiscale, multiscale finite elements, etc.), structure preserving numerical methods, stochastic optimization, analysis of machine learning methodologies, multilevel methods, scale-bridging and
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possible. It is strictly required that you have experience with: Scientific programming, preferably in python and/or MATLAB and/or C++ Derivation and implementation of finite element methods (FEM) in code
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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the muscle architecture of the larva within the generative process. We recently extracted the muscles of the Drosophila larva body from a CT-scan recording. Furthermore, we developed a finite element
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, applied mathematics, computer science, or related field. • Minimum of 2 years of directly related experience. • Experience with nondestructive inspection experimental methods. • Experience with modeling
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) + Finite element methods for complex flows in porous media (generalized multiscale finite elements via autoencoders, adaptive in space and time, splitting methods, and variational flux recovery) + Adaptive r