Physics Expert – Remote

RemoteJobsOne; Atlanta (GA); Remote; USD 110,000 - 220,000; Part time

Job summary

RemoteJobsOne seeks Physics Experts (Biophysics / Statistical Physics) for a fully remote, contract-based role. You will model bacterial population growth and stochastic switching to inform AI training data and system behavior.

Candidates with deep expertise in statistical physics, two-state Markov models, and Euler-Lotka analyses will contribute to research-level tasks, with assignments including Solver, Auditor, or Adjudicator as needed.

Qualifications

• Advanced expertise in statistical physics, biophysics, or related quantitative biological modeling of stochastic processes.
• Proven experience with two-state Markov models and gamma-distributed waiting times in biological or physical systems.
• Strong command of Euler-Lotka, perturbative expansions, and renewal theory for growth dynamics.

Responsibilities

• Analyze and model stochastic two-state processes in bacterial population dynamics.
• Apply Euler-Lotka to assess asymptotic growth rates under noise regimes.
• Develop perturbative expansions for small division-noise variance.
• Incorporate renewal theory and first-passage-time analysis to derive growth insights.
• Document methods and findings clearly for AI training purposes.

Skills

Statistical physics

Biophysics

Stochastic processes

Two-state Markov models

Euler-Lotka equation

Renewal theory

First-passage-time analysis

Population dynamics

Job description

This is a fully remote position, open to candidates based in 55 countries, including United States, United Kingdom, Canada, Germany, India, France, Netherlands, Singapore.

Pay: $80–$160/hr

Role Title: Physics Expert (Biophysics / Statistical Physics)

Role Type: Contractor

Location: Remote

We are 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

1. Analyze and model stochastic two-state Markov processes with gamma-distributed waiting times in the context of bacterial population dynamics.
2. Apply the Euler-Lotka equation to assess and benchmark asymptotic population growth rates under varying noise regimes.
3. Develop or review analytical approaches using perturbative expansions in small division-noise variance and validate resulting predictions.
4. Integrate renewal theory and first-passage-time analysis to derive key insights on population growth and cell-size regulation noise.
5. Document detailed methodological steps, assumptions, and findings clearly for AI training and reproducibility purposes.

Preferred Qualifications

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