Physics Expert (Biophysics / Statistical Physics)

Pay$80–$160/hr
Platformmicro1
EligibilityEligibility not confirmed — check platform
CategoryScience
CommitmentAI training project
First seen2026-08-02
Continue to role on micro1 → Check my fit

You apply on micro1's own site. Some outbound links carry disclosed referral codes; ranking is by fit, never payout.

Your saved fit

Match this role to see a fit summary.

Role listing · Source feed last seen 2026-09-15. Feed activity is not a guarantee that a vacancy is still open.

About this opportunity

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.

Skills & domains

physicsstochastic two-state markov processes with gamma-distributed waiting timeseuler-lotka equationperturbative expansion in small division-noise variancerenewal theoryfirst-passage-time analysis

Similar roles

More on micro1

AI recruitment platform using AI-interview vetting. Hires experts across engineering, finance, legal, and healthcare for AI training projects. All micro1 roles →