The Materials Science Division (https://www.anl.gov/msd) of Argonne National Laboratory has one immediate postdoctoral opening in the use of computational modeling to investigate quantum materials.
The postdoctoral researcher will work on applying atomistic modeling algorithms and first principles software to study optically activated processes in materials, in particular to study the electronic states of spin-defects. The postdoctoral researcher will be collaborating extensively with theoretical and experimental researchers at Argonne working in the field of quantum information science, other national laboratories, as well as universities. The postdoctoral researcher will have access to the state-of-the-art computing platforms and will perform simulations that incorporate elements of machine learning and quantum computing.
Applicants should have proven expertise in the following:
- Density functional theory modeling of materials, or other electronic structure methods
- High-performance computing, scientific computing
- Large-scale code development in C, C++, Fortran, or Python
- Excellent communication and analytical skills
The candidate may show proven experience in the following:
- Calculation of excited state properties in materials (e.g., using many-body perturbation theory)
- Machine learning applied to first principles simulations (e.g., using Tensorflow, Keras)
- Quantum computing: variational quantum algorithms with applications in quantum chemistry, and quantum programming (e.g., using Qiskit)
Ability to work independently and in an interdisciplinary collaborative environment, in close collaboration with experimentalists, is expected. Typical candidates will be independent, motivated and ambitious individuals with a PhD in computational physics, chemistry, materials science, molecular engineering, or a related field.
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