Postdoctoral Scholar, Physics
Core
Modeling electrochemical reactions on surfaces and interfaces using first-principles density functional theory (DFT), grand canonical DFT (GC-DFT), microkinetic modeling, and machine learning methods to develop machine learning interatomic potentials (MLIPs).
Role type
Postdoctoral Scholar in Computational Physics
Builds
Theoretical models of heterogeneous catalysis
Domain
Physics / Computational Chemistry / Materials Science
Deliverable
production ML models
Required skills
DFT, GC-DFT, microkinetic modeling, machine learning methods, MLIP development
Preferred skills
theoretical heterogeneous catalysis expertise
Technologies
DFT, GC-DFT, machine learning frameworks
Responsibilities
Perform first-principles DFT and GC-DFT calculations; develop microkinetic models; create machine learning interatomic potentials
Seniority
Postdoctoral Researcher
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