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Ying Li

3 days ago

Postdoctoral Researcher Position in Machine-Learned Interatomic Potentials for Hybrid Organic–Inorganic Perovskites University of Wisconsin-Madison in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

United States

University

University of Wisconsin-Madison

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Keywords

Computer Science
Materials Science
Molecular Dynamics
Density Functional Theory
Piezoelectricity
Atomistic Simulation
Physics
Computational Materials Science
ML

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About this position

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.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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