About the job
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: Computational Particle & Nuclear Physics Expert
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week
Role Responsibilities
- Design graduate-level computational problems for AI to solve using real scientific software.
- Develop problems requiring strategic planning and multi-step workflows in Particle & Nuclear Physics.
- Test and refine problems against state-of-the-art AI models to achieve target difficulty.
- Utilize scikit-hep and other HEP Python tools for data analysis and simulations.
- Work independently to refine problem designs based on feedback.
- Collaborate asynchronously with teams to improve AI model performance.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- Proven proficiency with scientific software libraries, demonstrated through research publications or professional work.
- Strong Python skills for writing problem setups and solution validators.
- Ability to work in a Linux/terminal environment with remote compute sandboxes.
- Available for 15–20 hours/week.
Preferred
- Experience across multiple domains or tools.
- Familiarity with benchmark or evaluation design.
- Background in scientific teaching or exam/problem-set design.
- Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
- For any help or support, reach out to: [email protected]
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
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