We are seeking a postdoctoral researcher to develop the machine learning framework for glass fiber-matrix interphase considering wide range of resins and sizing chemistry; variability in interphase topology – monolayer versus multi-layer sizing; and pressure/temp/strain rate effects. Input data for the machine learning should be generated from all-atom and/or coarse-grain (CG) MD simulations.
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