Role:
The Quantum Chemist will drive efforts to discover, implement, test, and deploy hybrid quantum/classical algorithms for the prediction of chemical properties on near-term quantum circuit hardware. The Quantum Chemist will actively work with QC Ware clients (industrial customers and US federal funding agencies) to develop end-to-end workflows for the quantum solution of real-world chemistry problems. The overarching goal of this role is for the Quantum Chemist to find ways to solve serious chemistry problems on NISQ hardware, where the quantum computing solution offers a performance advantage.
Key Responsibilities
The chemistry simulations work at QC Ware Corp. is highly interdisciplinary, and has three primary components: (1) design of new quantum circuit algorithms to solve the electronic Schrödinger equation (2) embedding of these quantum circuit algorithms within highperformance hybrid quantum/classical workflows to address large-scale chemical systems (3) deployment of these hybrid quantum-classical workflows to solve critical domain problems in industrial chemistry applications. The exceptional candidate will have sufficient background to immediately attack two of these three areas, together with the zeal to grow into the third area within ~1 year of on-the-job training.
Qualifications
The ideal candidate will have the following qualifications.
Required
- Ph.D. in Computational Chemistry, Computational Condensed Matter Physics or similar field
- Demonstrated publication record in quantum chemistry applications and/or methods development projects
- Fluency with Python
- Zeal to learn new skills as-needed in mathematics, physics, computer science, and engineering to deliver high-quality technical solutions
- Ability to work independently and within a larger team
Preferred
- Experience with quantum circuit algorithms and programming, e.g., within Cirq, Qiskit, PyQuil, or similar
- Fluency with C++, CUDA, or other high-performance classical programming languages
- Demonstrated contributions to one or more major classical electronic structure codes
- Demonstrated experience in solving industrial chemistry problems using classical theoretical chemistry methodology
Compensation:
- Attractive cash salary and stock option package
- Health/vision/dental coverage for employees and dependents
- Option to work and publish with top-quality university and national lab collaborators.
Contact:
Rob Parrish, Head of Chemistry Simulations | rob.parrish@qcware.com
Background
QC Ware has an established and growing portfolio of near-term quantum algorithms for quantum chemistry applications. We particularly focus on hybrid quantum/classical algorithms that provide an end-to-end prediction of useful chemical properties such as excitation energies, oscillator strengths, and nuclear gradients, and that use extensive classical pre-computation to compress the “hard kernel” of the problem to the minimal-sized qubit problem. More details can be found in some of our recent papers:
- MC-VQE+AIEM – arXiv:1901.01234 – Extension of the variational quantum eigensolver (VQE) to even-handed treatment of excited states and transition properties, introduction of the ab initio exciton model (AIEM) as a means to treat systems with thousands of atoms with a few dozen qubits for suitable photochemistry problems.
- MC-VQE+AIEM Gradients – arXiv:1906.08728 – Application of the Lagrangian formalism of derivative theory in classical electronic structure to efficiently compute analytic nuclear gradients of MC-VQE+AIEM energies.
- QFD – arXiv:1909.08925 – Method between VQE and QPE that uses more parallel measurements to solve the electronic structure problem via a subspace ansatz of quantum basis functions that are classically diagonalized in postprocessing.
- Jacobi parameter optimization – arXiv:1904.03206 – semi-global numerical optimization procedure for VQE and QAOA quantum circuit parameter optimization.
We are part of a large collaborative research endeavor in quantum algorithms for photochemistry sponsored by the US Department of Energy (DoE), and involving collaborators at SLAC National Accelerator Laboratory, Oak Ridge National Laboratory, University of Pennsylvania, and Columbia University. We also deliver quantum algorithms solutions for quantum chemistry for a number of industrial and government clients.
