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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 17 days ago
and motivated postdoctoral research fellow with expertise in numerical analysis, numerical scientific computing (including high performance scientific computing), and finite element numerical methods
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of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration
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within Irksome. A Ph.D. in applied mathematics, computer/computational science, or a related discipline and knowledge of finite element methods and scientific computing is required. Prior experience with
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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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experience developing biological application an additional plus Experience coding / applying finite difference, finite element or finite volume methods Experience using optimization software such as GAMS
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the model, its numerical implementation in a finite element code, and its validation against experimental data in collaboration with experimental collaborators. You will also engage with the hub activities
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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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high-order numerical finite element methods and near real-time software for computational simulations involving cardiac ablation treatments for arrhythmias. Initial appointment is for one year, position
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arising from solid/fluid dynamics/geomechanics, and numerical methods for partial differential equations, especially finite difference methods and finite element methods, both theory and applications. A
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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate