Quantum Information Physicist for AI Model Training

Contribute AMO and quantum information expertise to a research-focused project that benchmarks and models quantum optical systems. The work centers on cascaded optical parametric amplifiers, SU(1, 1) interferometers, two-mode squeezing, and the impact of realistic loss on entanglement and noise. Deliverables will shape how advanced models learn and reason about frontier quantum optics concepts. Key Responsibilities

• Analyze and model cascaded optical parametric amplifiers and SU(1, 1) interferometric setups under realistic loss mechanisms.
• Apply Bogoliubov transformations and covariance-matrix methods to quantify quantum correlations and noise properties.
• Derive and interpret sideband photocurrent spectra using homodyne detection techniques.
• Model optical loss via fictitious beamsplitters, and benchmark models against theoretical and experimental scenarios.
• Use squeeze-parameter hyperbolic identities to characterize entanglement and squeezing performance in lossy systems.
• Contribute in one of several roles, including Solver, Auditor, or Adjudicator, with assignments matched to your subfield specialization, experience, and demonstrated hands-on ability with the specified methods.
• Provide clear, research-grade explanations and analyses that can be used to train and evaluate next-generation AI systems, no prior AI experience required.

• Advanced degree such as a PhD, or equivalent research experience, in AMO physics, quantum optics, or quantum information science preferred.
• Proven expertise with Bogoliubov transformations, covariance-matrix formalism, and quantum noise analysis.
• Hands-on familiarity with sideband photocurrent spectra and homodyne detection methods.
• Experience modeling quantum optical loss mechanisms, including using fictitious beamsplitter techniques.
• Demonstrated ability applying squeeze-parameter hyperbolic identities to characterize squeezing and entanglement, in practical research or experimental analysis.
• Experience with cascaded parametric amplifiers, SU(1, 1) interferometry, or two-mode squeezing is highly valued.

Work Terms

• Role type, contractor.
• Location, remote.
• Assignments and role (Solver, Auditor, Adjudicator) will be tailored to your subfield specialization, experience level, and demonstrated practical ability with the listed methods.
• No prior AI or machine learning experience required, domain knowledge in AMO and quantum information is the primary requirement.

Compensation Pay range: $80.00 to $160.00 per hour. Eligibility

• Must be able to work as an independent contractor in a remote engagement.
• Strong domain expertise in AMO physics, quantum optics, or quantum information science is required.