[Hiring] Stochastic Biophysics PhD - Expert @Mercor

Role Description

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Stochastic Biophysics Physicist (PhD)

Type: Contract

Compensation: $80–$110/hour

Location: Remote

Duration: 8 to 10 weeks

Commitment: 10 hours/week

Role Responsibilities

• Evaluate research-level physics problems in stochastic autocatalytic growth and related areas.
• Develop and solve complex problems using chemical master equation, branching processes, and other advanced methods.
• Review and audit completed work for accuracy and completeness in reaction-network dynamics.
• Collaborate with specialists to ensure independent verification of written reasoning.
• Work independently and asynchronously to meet deadlines without fixed hours.

Qualifications

• PhD in biophysics, statistical physics, applied mathematics, or a closely related field.
• Published work on stochastic growth or reaction-network dynamics.
• Verifiable publication record with first-author papers.
• Working proficiency with LaTeX, Python, SymPy, and Jupyter.
• English at B2 or above, including written reasoning.

Requirements

• Familiarity with an agentic coding extension in VS Code.

Application Process

• Apply and complete the attached form with basic information and research experience.
• Provide an arXiv ID or DOI of your own paper as proof.
• We verify your papers and authorship against the public record.
• Onboard directly or invited to a short live alignment call.
• A brief 30 to 45 minute assessment may be added if needed.

Resources & Support

• For details about the interview process and platform information, please check: Interview Process
• For any help or support, reach out to: [email protected]
• Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.