Key details
- Role type
- Contract
- Compensation
- $70/hr
- Work arrangement
- Remote
- Category
- science
- Confirmed requirements
- 4
About this role
Role Overview
Develop original, executable biology research problems that evaluate advanced AI systems in scientific computing. Your work will help create challenging benchmarks grounded in real scientific methods and coding workflows.
Key Responsibilities
- Create research problems in biology with a coding focus, drawing on published papers, Kaggle datasets, open-source repositories, or scenarios you design.
- Write clear scientific prompts based on the selected source material.
- Define grading criteria that establish what a correct answer must include.
- Test and calibrate tasks against advanced AI models, releasing tasks only when strong models fail more often than they succeed.
Qualifications
- PhD in biology, biological sciences, biochemistry, genetics, ecology, or a closely related field.
- Demonstrated expertise in at least two of these areas: ecology, biochemistry, and genetics.
- Working proficiency in Python, R, or another relevant scientific-computing language.
- Comfort using Git or GitHub and running code in Docker, as work is completed through a pull-request workflow with automated quality checks.
- Peer-reviewed publications are preferred.
- Scientific software or research engineering experience is preferred.
Work Terms
- Remote, hourly independent-contractor engagement.
- Six-week engagement with an immediate start date.
- Part-time commitment of at least 20 hours per week.
Compensation
$70 per hour.
Application Process
- Submit your resume and application form.
- Complete a 25-minute conversational interview covering your background, experience, and motivations.
- Receive an update within a few days regarding next steps and onboarding.
What to prepare before applying
- PhD in biology, biological sciences, biochemistry, genetics, ecology, or a closely related field
- Demonstrated depth in at least two subdomains: ecology, biochemistry, and genetics
- Working proficiency in Python, R, or another relevant programming language for scientific computing
- Comfortable with Git/GitHub and running code in Docker
These are the confirmed hard requirements. The Apply button routes you to the partner platform where you complete the application.