Postdoctoral Researcher In Machine-learned Interatomic Potentials Hybrid Organic–inorganic Perov

# Postdoctoral Researcher in Machine-Learned Interatomic Potentials for Hybrid Organic–Inorganic Perov Postdoc position
· Post Doctoral
· University of Wisconsin–Madison
· United States of America Position type:
Postdoc postdoctoral

Level:
Post Doctoral Language:
English## About the PositionI am actively identifying candidates for a postdoctoral researcher position in my group at the University of Wisconsin-Madison, focused on developing machine-learned interatomic potentials (MLIPs) for hybrid organic–inorganic perovskites (HOIPs). The project will combine MLIPs, density-functional theory, molecular dynamics, and machine learning to investigate finite-temperature phase behavior, structural dynamics, and electromechanical properties, building on our recent DFT–ML work on piezoelectric HOIPs.

This opportunity may be a strong fit for candidates with backgrounds in computational materials science, atomistic simulation, DFT, molecular dynamics, perovskites, or machine learning. Candidates should have hands-on experience developing, validating, and deploying MLIPs. I have attached a brief position summary. Interested candidates are welcome to send me a CV and a short note describing their research interests and relevant experience ase feel free to share this opportunity with suitable candidates.

UW-Madison Mechanical Engineering UW-Madison College of Engineering.## Research Interests
* Develop machine-learned interatomic potentials for hybrid organic–inorganic perovskites
* Investigate finite-temperature phase behavior, structural dynamics, and electromechanical properties## Required

Skills & Qualifications
* Hands-on experience developing, validating, and deploying machine-learned interatomic potentials