Stochastic Biophysics Physicist (PhD)

Role Overview

Contribute research-grade reasoning to a public benchmark designed to evaluate frontier AI systems on genuine physics research challenges. This remote role focuses narrowly on stochastic autocatalytic growth and reaction-network dynamics. Assignments are matched to your publication record and may involve creating research problems, solving them, reviewing completed work, or auditing it. Deliverables must include clear, complete written reasoning that another specialist can independently follow and verify.

Research Focus

Relevant expertise includes autocatalytic reaction cycles, the stochastic Hinshelwood cycle, chemical master equation processes, branching processes, circulant matrix spectra, transient oscillations toward balanced exponential growth, moment hierarchies for reaction networks, and generating-function methods. Experience with long-range dispersal, heavy-tailed jump processes, or front propagation in range expansions is also relevant and should be noted in your application.

Qualifications

• PhD in biophysics, statistical physics, applied mathematics, or a closely related field.
• Published research specifically on stochastic growth or reaction-network dynamics. Broad biophysics experience alone is not sufficient.
• Publications demonstrating at least one of these method areas: chemical master equations and the stochastic Hinshelwood cycle; multi-type branching processes and circulant matrix spectra; moment hierarchies for reaction networks; or generating-function methods.
• A verifiable record of three to five representative papers, preferably from the past five years, with arXiv IDs or DOIs. First-author work is strongly preferred.
• Working proficiency in LaTeX, Python, SymPy, and Jupyter. Familiarity with an agentic coding extension in VS Code is useful; disclose any gaps accurately.
• English proficiency at B2 level or above, including the ability to communicate written technical reasoning clearly.

Postdoctoral researchers, research scientists, and junior faculty are especially well suited. Senior PhD students with a strong first-author publication record may also apply.

Work Terms

• Remote, asynchronous work with no fixed hours.
• Commit approximately 10 hours per week for an 8 to 10 week period, starting immediately.
• Assignments are agreed after matching your background to the relevant research area.

Compensation

$80 to $110 per hour, determined by the depth of your subdomain fit.

Application Process

• Complete the application form with your education, research experience, method self-assessment, and relevant research area.
• Provide an arXiv ID or DOI for your own paper, along with your author position and the methods it demonstrates. Selections without supporting publication evidence are not scored.
• Your publications and authorship will be verified against the public record.
• Qualified candidates will either proceed directly or be invited to a short live alignment call to confirm the area and assignment.
• A 30 to 45 minute assessment may be requested when needed, though most applicants will not complete one.