We are looking for a highly motivated postdoctoral candidate to use theory, molecular simulation, and machine learning to understand how chemical functionalization of soft matter systems (e.g., colloids, polymers) affects their self-assembly into different structures. Recent work has shown how phase diagrams can be predicted for multicomponent colloidal assemblies using novel structure enumeration schemes based on symmetry [1,2]. This project will focus on extending previous work and connecting it with experimentally viable design routes to enable the rational design and synthesis of colloidal crystals, monolayers, and functional materials.
 “Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly,” N. A. Mahynski, E. Pretti, V. K. Shen, J. Mittal, Nature Commun., 10 2028 (2019).
 “Symmetry-based crystal structure enumeration in two dimensions,” E. Pretti, V. K. Shen, J. Mittal, N. A. Mahynski, J. Phys. Chem. A 124, 3276-3285 (2020).