Ying Li

University of Wisconsin-Madison is advertising postdoctoral and PhD openings in the Polymer Digital Engineering Lab within Mechanical Engineering. The research theme is multiscale modeling of polymers and polymer composites , spanning all-atom simulation , coarse-grained modeling , mesoscale methods , and potentially continuum mechanics . The lab emphasizes linking molecular-level physics to bulk material performance and using computational methods to design advanced polymeric materials. Research keywords: polymer physics, polymer composites, molecular dynamics, coarse-grained modeling, multiscale modeling, computational materials science, mechanics, finite element analysis, multiphysics, machine learning, data-driven simulation. Postdoctoral opening: candidates should have a PhD in a relevant engineering or science field and strong experience in micromechanics, computational polymer/materials physics, multiscale simulation, and related computational tools. Experience with massively parallel computing and software such as LAMMPS or GROMACS is preferred. PhD opening: applicants should have a BS in a closely related field; an MS with project experience and publications is a plus. Programming skills, parallel computing, molecular dynamics, finite element analysis, and broad knowledge of computational materials science/polymer physics are preferred. TOEFL and GRE scores are requested for PhD applicants. Funding: postdoctoral positions are financially supported for up to 3 years. PhD positions are supported through research assistant/teaching assistant funding. How to apply: email Dr. Ying Li with the requested documents. The postdoc call asks for a CV, cover letter, and references; the lab page also mentions a research statement and representative publications. The PhD call asks for a CV, transcripts, TOEFL/GRE scores, and references. Applications are reviewed on a rolling basis. Institution: University of Wisconsin-Madison, Department of Mechanical Engineering.

University of Wisconsin-Madison is seeking a postdoctoral researcher in the group of Ying Li (Associate Professor) to work on machine-learned interatomic potentials (MLIPs) for hybrid organic–inorganic perovskites (HOIPs) . The project combines MLIPs , density-functional theory (DFT) , molecular dynamics , and machine learning to study finite-temperature phase behavior , structural dynamics , and electromechanical properties . The post mentions that the work builds on recent DFT–ML research on piezoelectric HOIPs . This opportunity is a strong fit for candidates with training in computational materials science , atomistic simulation , DFT , molecular dynamics , perovskites , or machine learning . Applicants should have hands-on experience developing, validating, and deploying MLIPs. To apply, send a CV and a short note describing your research interests and relevant experience to [email protected] . No deadline or funding details are stated in the post. Institution: University of Wisconsin-Madison, Mechanical Engineering / College of Engineering.