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Why this grade This listing scored 29/100, which is an F. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 10 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-20 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
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.
Originally posted on Himalayas
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Where this listing came from
- 02 Aug 2026 Himalayas first sighting
Seen on 1 board over 31 days.