Quantum Computing Materials Science Intern
About The Position
As an intern in the Atomistic Computational Materials Science team at the Bosch Research and Technology Center North America, you will contribute to the development of advanced computational methods for strongly correlated electron systems within a hybrid quantum–classical Dynamical Mean-Field Theory (DMFT) workflow. Your work will focus on the development and benchmarking of: (1) classical impurity solvers based on Density Matrix Renormalization Group (DMRG) and Adaptive Sampling Configuration Interaction (ASCI), and (2) quantum impurity solvers based on Variational Quantum Eigensolver (VQE), quantum Equation of Motion (qEOM), Subspace Expansion (SE), and Sample-based Quantum Diagonalization (SQD). These methods will be used to compute ground and excited states of multi-orbital Anderson Impurity Model (AIM) Hamiltonians, evaluate Green’s functions in the Lehmann representation, and integrate the solvers into a hybrid DMFT self-consistency workflow as described in npj Comput. Mater. 11, 325 (2025) and arXiv:2404.09527. The goals of this research are to enable scalable simulations of strongly correlated materials and to assess the role of emerging quantum computing technologies in future industrial materials design workflows. You will have access to state-of-the-art high-performance computing infrastructure and classical quantum simulators for algorithm development and benchmarking.
Requirements
- Currently pursuing a PhD in Physics, Chemistry, Materials Science, Applied Mathematics, or a related field
- Strong background in quantum many-body physics, electronic structure theory, or quantum algorithm development
- Experience with numerical simulations (Python, NumPy, SciPy)
- Research experience, strong teamwork skills, and excellent oral and written communication
- Minimum GPA of 3.0
Nice To Haves
- Experience with DMRG, tensor networks, or selected CI methods (e.g., ASCI)
- Familiarity with DMFT and classical or quantum impurity solvers
- Experience with quantum computing frameworks (Qiskit, Cirq, PennyLane)
- Knowledge of quantum algorithms for ground and excited states (VQE, qEOM, subspace methods, SQD, imaginary-time approaches)
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
