AMO / Quantum Information Physicist for AI Training

Role Overview

Apply advanced AMO and quantum information expertise to help train next-generation AI systems through research-focused benchmarking of quantum-optical concepts. This work focuses on cascaded optical parametric amplifiers, SU(1, 1) interferometers, loss effects, and two-mode squeezing. Assignments may involve Solver, Auditor, or Adjudicator work, matched to your specialization, experience, and demonstrated hands-on capability with the required methods. Prior AI experience is not required.

Key Responsibilities

• Analyze and model cascaded optical parametric amplifiers and SU(1, 1) interferometric systems under realistic loss mechanisms.
• Use Bogoliubov transformations and covariance-matrix methods to quantify quantum correlations and noise properties.
• Derive and interpret sideband photocurrent spectra using homodyne-detection methods.
• Implement and evaluate loss models based on fictitious beamsplitters, benchmarking them against theoretical and experimental scenarios.
• Apply squeeze-parameter hyperbolic identities to characterize entanglement and squeezing performance in lossy quantum systems.

Qualifications

• Advanced degree, PhD or equivalent experience, in Atomic, Molecular, and Optical Physics, Quantum Optics, or Quantum Information Science.
• Proven expertise in physics, Bogoliubov transformations, covariance-matrix formalism, and quantum-noise analysis.
• Hands-on familiarity with sideband spectra, homodyne detection, and quantum-optical loss modeling.
• Demonstrated practical research or experimental-analysis experience applying squeeze-parameter hyperbolic identities.
• Experience with cascaded parametric amplifiers, SU(1, 1) interferometry, or two-mode squeezing is highly valued.

Work Terms

• Remote contract engagement.

Compensation

• $80 to $160 per hour.