Math PhD Computational Scientist – Part-Time AI Benchmarking

RemoteLeads; Northern (KY); Hybrid; USD 80,000 - 113,000; Part time

Benefits offered by this job

Six-week engagement

Accommodations available

Job summary

RemoteLeads seeks a highly qualified researcher to work part-time for six weeks at 20+ hours per week, starting immediately. The role focuses on creating scientific computing prompts, grading criteria, and benchmarking AI models against frontier challenges.

Proficiency in Python or R is required, with a PhD in a relevant field and strong computational background. Candidates should be comfortable with Git and Docker, and prior research engineering or peer-reviewed publications are a plus.

Qualifications

• PhD in mathematics, applied mathematics, computational mathematics, or closely related field.
• Depth in at least two of numerical linear algebra, computational mechanics, and computational finance.
• Working proficiency in Python or R for scientific computing.
• Comfort with Git/GitHub and running code in Docker.
• Peer‑reviewed journal publications preferred.
• Prior scientific software or research engineering experience preferred.
• Availability for part-time work of 20+ hours per week over six weeks.
• Ability to start immediately.

Responsibilities

• Source material from research papers, Kaggle datasets, open-source repositories, or original scenarios.
• Write scientific computing prompts based on the selected material.
• Develop grading criteria that define correct solutions.
• Calibrate tasks against frontier AI models and release them only when models frequently fail.
• Submit authored work through a GitHub pull-request workflow with automated quality checks.

Skills

Python

R

GitHub

Docker

Education

PhD in mathematics / applied mathematics / computational mathematics

Tools

Git

Docker

Job description

RemoteLeads seeks a highly qualified researcher to work part-time for six weeks at 20+ hours per week, starting immediately. The role focuses on creating scientific computing prompts, grading criteria, and benchmarking AI models against frontier challenges.

Proficiency in Python or R is required, with a PhD in a relevant field and strong computational background. Candidates should be comfortable with Git and Docker, and prior research engineering or peer-reviewed publications are a plus.