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

ScholarLink Inc.; Madison (WI); Presencial; USD 60.000 - 76.000; Jornada completa

Descripción de la vacante

University of Wisconsin–Madison invites applications for a Postdoctoral Researcher in Machine-Learned Interatomic Potentials for Hybrid Organic–Inorganic Perovskites. The position combines MLIPs, DFT, MD, and ML to study finite-temperature phase behavior and electromechanical properties.

Candidates should have hands-on experience developing, validating, and deploying MLIPs and a background in computational materials science or related fields.

Formación

• Hands-on experience developing, validating, and deploying machine-learned interatomic potentials.

Responsabilidades

• Develop machine-learned interatomic potentials for HOIPs.
• Investigate finite-temperature phase behavior, structural dynamics, and electromechanical properties.

Conocimientos

Hands-on experience developing inter-

Herramientas

Density Functional Theory (DFT)

Molecular Dynamics

Machine Learning

Descripción del empleo

# Postdoctoral Researcher in Machine-Learned Interatomic Potentials for Hybrid Organic–Inorganic PerovPostdoc position·Post Doctoral·University of Wisconsin–Madison·United States of AmericaPosition type: Postdoc postdoctoralLevel: Post DoctoralLanguage: 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 at [e-mail]. Please 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