About this Physics Expert (Biophysics / Statistical Physics) role at micro1
Role Title: Physics Expert (Biophysics / Statistical Physics)
Role Type: Contractor
Location: Remote
micro1 is engaging Physics Experts (Biophysics / Statistical Physics) to contribute to a research-level project focused on modeling bacterial population growth, stochastic two-state growth-rate switching, cell-size regulation noise, and asymptotic population growth rate. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
No prior experience in AI is required — your domain knowledge is what matters. Participants may be considered for one or more assignments, including Solver, Auditor, or Adjudicator, based on subfield specialization, seniority, and hands-on experience with the relevant methods.
Scope of Work
- Analyze and model stochastic two-state Markov processes with gamma-distributed waiting times in the context of bacterial population dynamics.
- Apply the Euler-Lotka equation to assess and benchmark asymptotic population growth rates under varying noise regimes.
- Develop or review analytical approaches using perturbative expansions in small division-noise variance and validate resulting predictions.
- Integrate renewal theory and first-passage-time analysis to derive key insights on population growth and cell-size regulation noise.
- Document detailed methodological steps, assumptions, and findings clearly for AI training and reproducibility purposes.
Preferred Qualifications
- Advanced expertise in statistical physics, biophysics, or related quantitative biological modeling of stochastic processes.
- Proven experience working 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 in the context of population or growth dynamics.
- Demonstrated ability to conduct first-passage-time analysis and interpret implications for growth-rate fluctuations and size control.
