Mathematics PhD Coding Experts

Accountabilities:

• • Source relevant scientific material from published research, Kaggle datasets, open-source repositories, or original scenarios to develop challenging computational problems.
  • Design original scientific prompts that require meaningful mathematical reasoning and executable solutions.
  • Create clear, rigorous grading criteria that define what constitutes a correct and high-quality solution.
  • Develop tasks with a strong coding focus across relevant mathematical domains such as numerical linear algebra, computational mechanics, and computational finance.
  • Execute and validate submitted code to ensure that tasks are technically sound, reproducible, and appropriately challenging.
  • Calibrate tasks against advanced AI models, refining them until they reliably distinguish between strong and unsuccessful model performance.
  • Apply deep subject-matter expertise to ensure that evaluation tasks accurately reflect real scientific and computational challenges.
  • Collaborate through a structured Git/GitHub and pull-request workflow, following automated quality checks and technical standards.

  Requirements:

  • PhD in Mathematics, Applied Mathematics, Computational Mathematics, or a closely related discipline.
  • Demonstrated depth and expertise in at least two of the following areas: numerical linear algebra, computational mechanics, and computational finance.
  • Working proficiency in Python or R for scientific computing and computational problem-solving.
  • Strong understanding of mathematical modeling, numerical methods, and scientific computation.
  • Comfortable working with Git/GitHub, including pull requests and version-controlled workflows.
  • Experience running and validating code in Docker or similar containerized environments.
  • Ability to translate complex mathematical and scientific concepts into precise, executable programming challenges.
  • Strong analytical and problem-solving skills, with exceptional attention to technical accuracy and rigor.
  • Ability to work independently, manage priorities, and deliver high-quality research tasks within defined timelines.
  • Preferred: Peer-reviewed publications demonstrating research depth in relevant mathematical or computational fields.
  • Preferred: Previous experience in scientific software development, research engineering, or computational research.

  Benefits:

  • Fully remote: Work from anywhere in Canada and complete the engagement on your own schedule.
  • Flexible part-time commitment: Approximately 20+ hours per week.
  • 6-week engagement: Immediate start with the possibility of projects being extended, shortened, or concluded early depending on project needs and performance.
  • Independent contractor arrangement: Work as a contractor with flexibility and autonomy.
  • Weekly payments: Compensation paid weekly through Stripe or Wise based on services delivered.
  • AI and research impact: Apply your mathematical expertise to projects focused on evaluating and improving advanced AI systems.
  • Research-driven work: Collaborate on challenging scientific computing tasks designed to push the capabilities of frontier AI models.
  • Referral opportunity: Eligible participants can earn up to $280 per successful referral, subject to applicable restrictions.
  • Privacy and confidentiality: Projects are designed without requiring access to confidential or proprietary information from previous employers, clients, or institutions.
  • Important eligibility note: H-1B and STEM OPT candidates are not currently supported for this engagement.