Postdoctoral Appointee - NST Computational Modeling and Machine Learning
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7199758 (Ref #: 416937)
- Posting Date: Dec 8, 2023
Job Description
The Center for Nanoscale Materials (https://www.anl.gov/cnm) at Argonne National Laboratory has an immediate opening for a Postdoctoral Appointee in the use of computational modeling and machine learning to interpret experimental x-ray, electron, and scanning probe characterization data, especially for energy materials. The postdoctoral researchers will work within the group of Dr Maria Chan (https://www.anl.gov/profile/maria-k-chan) on developing and applying algorithms and software for the use of first principles and atomistic modeling, together with machine learning, to accelerate the inversion of experimental characterization data, especially x-ray spectroscopies.
Position Requirements
- A PhD completed within the last 3 years or soon to be completed; in Physics or a related field
- Density functional theory modeling of materials, e.g. high throughput calculations, structure prediction, classical and ab initio MD simulations
- Simulation of experimental characterization signals, e.g. x-ray spectroscopy, electron microscopy, scanning tunneling microscopy, and neutron scattering
- Use of machine learning approaches
- Development and implementation of algorithms and software for materials modeling
- High-performance and parallel computing
- Excellent communication and analytical skills
- Ability to work independently and in an interdisciplinary collaborative environment, in close collaboration with experimentalists.
- Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
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