Queracomputinginc

Queracomputinginc

Quantum Scientist - AMO Theory and Device Modeling

Boston, MA, USA

Sponsorship not specified$130k-$212kDetected 23 days ago
Python

About the role

  • The approximate base salary range for this position is $130,400 - $211,900.
  • We consistently monitor external market data and update base salary ranges accordingly.
  • In addition to our base salary offerings, we also provide equity grants for all new hires.

Requirements

  • Experience modeling AMO experiments, including realistic multi-level atomic structure calculations, light-matter interactions, and Rydberg physics.
  • Basic knowledge of quantum error correction methods and quantum algorithms.
  • Proficiency in Python and/or Julia for scientific modeling and simulation.
  • PhD in theoretical atomic, molecular, and optical (AMO) physics or a closely related field.
  • Demonstrated ability to collaborate productively with experimental AMO or quantum hardware groups.
  • Strong publication record in AMO physics or other relevant areas of quantum science.

Nice to have

  • Experience modeling noise sources, imperfections, and decoherence in neutral-atom platforms.
  • Hands-on experience with open quantum systems simulations.
  • Experience with pulse-level control, Hamiltonian engineering, and quantum control/optimization.
  • Familiarity with benchmarking and characterization of quantum hardware primitives.
  • Experience translating physical noise models into logical-level performance metrics.
  • We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience.
  • QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer.

Compensation

  • The approximate base salary range for this position is $130,400 - $211,900.
  • We consistently monitor external market data and update base salary ranges accordingly.

This listing is sourced directly from Queracomputinginc's careers page and normalized into a canonical job model.