Computational Materials Scientist - Postdoctoral Researcher
Core
Develop multicomponent thermodynamic and kinetic databases and integrate ICME microstructure evolution models into a Materials Acceleration Platform to design structural alloys for extreme environments.
Role type
Postdoctoral Researcher (Computational Materials Science)
Builds
Multicomponent thermodynamic/kinetic databases and ICME microstructure evolution models
Domain
Materials Science / Computational Thermodynamics / Nuclear Materials
Deliverable
production ML models
Required skills
CALPHAD, microstructure and property modeling, uncertainty quantification, ICME, alloy design, design of experiments, thermodynamics, phase stability, phase transformations, defect structures, solidification, thermo-mechanical processing
Preferred skills
Super Intelligence (AI), machine learning, Bayesian optimization, black-box optimization, gradient-based optimization, phase field, cellular automata, Monte Carlo method, continuum models
Technologies
Thermo-Calc, Pandat, FactSage, PyCalphad, Thermochimica, OpenCalphad
Responsibilities
Independently develop multicomponent thermodynamic and kinetic databases; Incorporate ICME microstructure evolution models and property predictions into the Materials Acceleration Platform; Develop uncertainty quantification and propagation methods; Interface with experimentalists in design of experiment and material development campaigns; Publish research results in peer-reviewed scientific journals and present results at external conferences.
Seniority
Postdoctoral (early career, PhD within 5 years)