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Mathematics PhD Coding Experts

πŸ“… Sep 14
MathematicsNumerical Linear AlgebraComputational MechanicsComputational Finance
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πŸ“œ Description

  • Source material from published papers, Kaggle datasets, open-source repositories, or original scenarios.
  • Write scientific prompts based on the source material.
  • Create grading criteria that define correct answers.
  • Calibrate tasks against frontier models, shipping only when strong models fail more often than they succeed.

πŸ› οΈ Requirements

  • Mathematics β€” numerical linear algebra, computational mechanics, computational finance
  • PhD in mathematics, applied mathematics, computational mathematics, or a closely related field
  • Demonstrated depth in at least two of the following subdomains: numerical linear algebra, computational mechanics, computational finance
  • Working proficiency in Python or R for scientific computing
  • Comfortable with Git/GitHub and running code in Docker β€” authoring runs through a pull-request workflow with automated quality checks
  • Publications in peer-reviewed journals
  • Prior scientific software or research engineering experience
Full job description

This role is for one of our clients

Compensation: $70 per hour

We are hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code)

We are partnering with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

Domains - depth required in at least two subdomains (with a coding focus)

  • Mathematics β€” numerical linear algebra, computational mechanics, computational finance

Requirements

What you'll do

  • Source your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design
  • Write scientific prompts based on the input
  • Build the grading criteria that define a correct answer
  • Calibrate against frontier models β€” a task ships only when strong models fail it more often than they succeed

Required

  • PhD in mathematics, applied mathematics, computational mathematics, or a closely related field
  • Demonstrated depth in at least two of the following subdomains: numerical linear algebra, computational mechanics, computational finance
  • Working proficiency in Python or R for scientific computing
  • Comfortable with Git/GitHub and running code in Docker β€” authoring runs through a pull-request workflow with automated quality checks

Preferred

  • Publications in peer-reviewed journals
  • Prior scientific software or research engineering experience

Engagement

  • Duration: 6 weeks
  • Commitment: part-time, 20+ hours per week
  • Start date: immediate

Process

  1. Upload your resume and application form
  2. A 25-minute conversational interview covering your background, experience, and motivations
  3. Follow up within a few days with next steps and onboarding

Apply today and put your research expertise to work building the next generation of scientific AI.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

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