Location: Palo Alto, California

Quantum Engineer Role:


The Quantum Engineer will drive efforts to discover, implement, test, and deploy hybrid quantum/classical algorithms for the prediction of properties of 3D periodic materials on near-term quantum circuit hardware. The Quantum Engineer 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 materials science problems. The overarching goal of this role is for the Quantum Engineer to find ways to solve serious materials science problems on NISQ hardware, where the quantum computing solution offers a performance advantage.

Getting in on the ground floor means that you can ride the next wave of technological innovation and investment.

QC Ware is seeking to add an experienced Product Manager to strategic lead the way we go to market. The new hire will be based in Palo Alto, CA.

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 high performance hybrid quantum/classical workflows to address large-scale chemical and solid state systems (3) deployment of these hybrid quantum-classical workflows to solve critical domain problems in industrial chemistry and materials science 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 similarfield.
  • Demonstrated publication record in quantum chemistry or materials science applications and/or methods development projects.
  • Experience with developing classical periodic quantum chemistry methods or embedding techniques such as DMFT or DMET.
  • Expertise with classical periodic electronic codes such as VASP or Quantum Espresso.
  • 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.

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 post processing.
  • 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.

Contact Info:

 

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