Interested candidates should submit the required application materials to Das Pemmaraju (email@example.com) with the title “SIMES-NPNEQ Postdoctoral Fellowship”.
The Stanford Institute for Materials and Energy Sciences (SIMES) invites applications for a postdoctoral fellowship in the area of computational materials science. This position is associated with the newly established multi-institutional center for Non-Perturbative Studies of Functional Materials under Non-Equilibrium Conditions (NPNEQ) which aims to enable predictive simulations of materials far from equilibrium to inform research in quantum materials and attosecond strong-field physics. The successful candidate will work as a member of the NPNEQ team on the theory, numerical implementation and validation of the next generation of real-time time-dependent density functional theory (TDDFT) methods for scalable nonequilibrium dynamics simulations on emerging exascale supercomputers.
The postdoc will be based at SIMES which is a joint institute between the SLAC National Accelerator Laboratory and Stanford University and home to a number of cutting-edge experimental and theory programs in ultrafast materials science (http://simes.stanford.edu/). Within SIMES, the postdoc will work under the supervision of Dr. Das Pemmaraju and Prof. Aaron Lindenberg. Furthermore, as a member of the NPNEQ center the postdoc will work in close collaboration with theory and experimental teams at Stanford/SLAC National Accelerator Laboratory, Lawrence Livermore National Laboratory and Lawrence Berkeley National Laboratory.
- Applicants should have a PhD or equivalent qualification in physics, mathematics, chemistry, materials science or a related discipline.
- Experience in quantum simulation methods such as density functional theory, time-dependent density functional theory, many-body perturbation theory, Quantum Monte Carlo or related approaches is highly desirable.
- This position involves a significant amount of numerical code development aimed at the next generation of exascale supercomputers.
- Therefore, the ideal candidate will have prior scientific programming experience combined with an enthusiasm for scalable computing on highly parallel architectures.
- Additionally, the candidate would have demonstrated written and verbal communication skills in an academic setting along with an ability to work both individually and in a collaborative team environment.
- Up-to-date CV
- Statement of research interest