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relate to our team’s ongoing cutting-edge research directions, including Finite element modeling Positron emission tomography/magnetic resonance (PET/MRI) imaging Magnetic resonance (MR) diffusion imaging
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knowledge of numerical methods - knowledge of free-surface flows, granular flows - proven experience in numerical simulation (finite elements, finite volumes, CFD, LES, etc.) - proficiency in basic scientific
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Mathematics, Applied Mechanics, or related disciplines (a minimum honours degree at UK first or upper second-class level) Experience in computational fluid dynamic/finite element modelling by using commercial
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manufacturing, thermomechanical simulations, and process modeling (prior experi- ence in finite element analysis, computational thermodynamics, or residual stress modeling will be advantageous) Solid
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evaluation of alloys; familiarity with finite element methods. Skills and experience in programming, machine learning, or signal processing are all considered a plus. Outstanding UA benefits include health
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access
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computational mathematics (e.g., finite elements, reduced-order models). Co-develop open-source tools, educational notebooks, and visual interfaces for mathematical exploration and experimentation. Publish
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will be to: Model the optical, mechanical and optoelectronic properties of the fibers using ray tracing and finite element method models; Select and characterize soft materials for the fibers, and use
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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, or AI/ML applications in engineering Demonstrated experience with digital twin development, finite element analysis (FEA), or data-driven manufacturing tools Preferred: Experience working in