Material Science PhD Coding Experts

Weekday AI

United States

À distance

USD 83 000 - 110 000

Temps partiel

14 jours+
Générateur de candidature

Une candidature complète en une minute — un CV et une lettre de motivation personnalisés, prêts à envoyer.

Passez les filtres ATS

Résumé du poste

Mercor is 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.

We are hiring PhD and Master’s scientists to define domains, source data, write prompts, and build rigorous grading criteria. This fully remote contract runs for 6 weeks at 20+ hours per week, with compensation of $70 per hour.

Qualifications

  • PhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field.
  • Depth in semiconductor materials and molecular modeling.

Responsabilités

  • Source 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 — a task ships only when strong models fail it more often than they succeed.

Connaissances

Python
R
Git/GitHub
Docker

Formation

PhD in materials science

Outils

Docker

Description du poste

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)

Mercor is 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)

  • Materials science — semiconductor materials, molecular modeling

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 — a task ships only when strong models fail it more often than they succeed

Required

  • PhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field
  • Demonstrated depth in both of the following subdomains: semiconductor materials and molecular modeling
  • Working proficiency in Python, R, or another relevant programming language for scientific computing
  • Comfortable with Git/GitHub and running code in Docker — 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.

Contract and Payment Terms

  • You will be engaged as an independent contractor.
  • This is a fully remote role that can be completed on your own schedule.
  • Projects can be extended, shortened, or concluded early depending on needs and performance.
  • Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
  • Payments are weekly on Stripe or Wise based on services rendered.
  • Please note: We are unable to support H1-B or STEM OPT candidates at this time.
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