Biophysics / Statistical Physics Physicist for AI Training

Role Overview

Apply research-level expertise in biophysics and statistical physics to help develop high-quality inputs that improve how next-generation AI systems learn, reason, and perform. This remote contract role focuses on bacterial population growth, stochastic two-state growth-rate switching, cell-size regulation noise, and asymptotic population growth rates. No prior AI experience is required, your subject-matter expertise is the focus.

Key Responsibilities

• Analyze and model stochastic two-state Markov processes with gamma-distributed waiting times in bacterial population dynamics.
• Apply the Euler-Lotka equation to evaluate and benchmark asymptotic population growth rates across noise regimes.
• Develop or review analytical methods using perturbative expansions in small division-noise variance, and validate resulting predictions.
• Use renewal theory and first-passage-time analysis to derive insights into population growth and cell-size regulation noise.
• Clearly document methodological steps, assumptions, and findings to support AI training and reproducibility.

Qualifications

• Advanced expertise in statistical physics, biophysics, or related quantitative biological modeling of stochastic processes.
• Experience with two-state Markov models and gamma-distributed waiting times in biological or physical systems.
• Strong command of the Euler-Lotka equation, perturbative expansions, and renewal theory for population or growth dynamics.
• Demonstrated ability to conduct first-passage-time analysis and interpret its implications for growth-rate fluctuations and size control.

Work Terms

• Remote contract engagement.
• Qualified participants may be considered for Solver, Auditor, or Adjudicator assignments based on subfield specialization, seniority, and hands-on experience with the relevant methods.

Compensation

$80 to $160 per hour.