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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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, Python, Julia, or MATLAB Knowledge in numerical methods and simulation, particularly for partial differential equations and finite element methods Basic understanding of mathematical modeling with and/or
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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