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Field
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this is stochastic models in infinite dimensional spaces, applications in shape analysis, and numerical implementations of the developed models. The postdoc project will span between these areas with a
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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operation in microgravity. Perform numerical modeling analysis to test and refine microfluidic devices and establish suitable data analysis tools. Advise and mentor graduate and undergraduate students on
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of the appointment. Preferred Qualifications: Candidates with strong backgrounds in kinetic equation, numerical analysis, scientific computing, PDE together with research experience in scientific
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-validate the experimental and numerical platforms of the mechanics informatics framework. On the experimental side, this involves designing and fabricating heterogeneous specimens, conducting multiaxial
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materials, supported by an NSF CMMI CDS&E award and industry-sponsored projects. The primary function of the position is to develop and cross-validate the experimental and numerical platforms of the
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and delay-differential equations. Scientific computing and numerical analysis Large-scale dynamical systems High-performance computing Parallel numerical algorithms GPU computing Strong programming
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working on developing experimental and numerical methods for wind turbine aerodynamics. The particular areas of responsibilities include: High and low-fidelity modelling of wind turbine airfoil and
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, international team working on developing experimental and numerical methods for wind turbine aerodynamics. The particular areas of responsibilities include: Modelling of rotor aerodynamics with both low
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a range of topics including: Coastal hydrodynamic and morphodynamic numerical modeling. Field data collection and analysis of nearshore dynamics. Design and analysis of flood control infrastructure