Physics Expert

RemoteJobsOne; Brussel; À distance; EUR 97 000 - 194 000; Temps partiel

Résumé du poste

RemoteJobsOne is seeking a Physics Expert (Biophysics / Statistical Physics) for a fully remote contractor role based in Belgium. You will model bacterial population dynamics and growth-rate fluctuations, applying stochastic methods and renewal theory to inform AI training datasets.

Preferred candidates have deep expertise in statistical physics and biophysics, with hands-on experience in two-state Markov models.

Qualifications

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

Responsabilités

• 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 detailed methodological steps for AI training and reproducibility.

Connaissances

Statistical physics

Biophysics

Two-state Markov models

Gamma waiting times

Description du poste

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

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.