Physics Expert

RemoteJobsOne; Amsterdam; Remote; EUR 117,000 - 194,000; Part time

Job summary

RemoteJobsOne is seeking a Physics Expert (Biophysics / Statistical Physics) for remote contractor work on a research-level project. You will model bacterial population dynamics, explore growth-rate switching, and contribute to AI training inputs with high-quality, real-world data.

Responsibilities include developing Markov-based models, applying Euler-Lotka analysis, and performing first-passage-time studies to quantify growth and size regulation under noise.

Qualifications

• Advanced expertise in statistical physics, biophysics, or related quantitative biological modeling.
• Experience with two-state Markov models and gamma-distributed waiting times in biological or physical systems.
• Strong knowledge of the Euler-Lotka equation, perturbative expansions, and renewal theory.
• Ability to perform first-passage-time analysis and interpret implications for growth dynamics.

Responsibilities

• Analyze and model stochastic two-state Markov processes with gamma-distributed waiting times.
• Apply Euler-Lotka equation to assess asymptotic growth rates under noise regimes.
• Develop or review analytical approaches using perturbative expansions with small division-noise variance.
• Integrate renewal theory and first-passage-time analysis to derive insights on growth and size control.
• Document methods, assumptions, and findings for AI training and reproducibility.

Skills

Statistical physics

Biophysics

Stochastic modeling

Two-state Markov models

First-passage-time analysis

Euler-Lotka equation

Renewal theory

Job description

This is a fully remote position, open to candidates based in Netherlands.

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.