Postdoctoral Appointee – ML-Accelerated Electronic Structure Modeling of 2D Materials (CNM)
UChicago Argonne(3 months ago)
About this role
A postdoctoral appointment in the Theory and Modeling Group at Argonne National Laboratory focused on theory and simulation of the electronic structure of polycrystalline and defective two-dimensional materials. The work centers on developing machine-learning surrogates for electronic structure and electrostatic potential within a multi-institution collaboration to predict structural and electronic evolution under applied bias.
Required Skills
- Electronic Structure
- DFT
- Machine Learning
- Tight-Binding
- Continuum Models
- High-Throughput
- Database Management
- Software Development
- Workflow Automation
- Collaboration
+1 more
Qualifications
- PhD in Physics, Chemistry, Materials Science, Electrical Engineering, or Related Field
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