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on the microlocal analysis of the problem, an efficient alternative to the standard Finite Element approach can be designed. The main aim of this postdoctoral project will be to adapt the methods developed so far
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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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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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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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methods (e.g., AFM, Nano-IR, STM, SECCM, SICM, SECM), advanced light and electron microscopy, materials synthesis (e.g., conductive metal-organic frameworks, 2D/hierarchical structures, nanoparticles
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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
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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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finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the
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measurements, and load measurements. Proficiency in computational methods, such as finite element analysis (FEA) and computational fluid dynamics (CFD). Experience with data acquisition and analysis using