Materials Science Coding Expert (Remote | $70/hr)

Original job posting

Author and develop rigorous, executable scientific computing problems and grading criteria to evaluate frontier AI models in materials science. Source original research material and calibrate tasks to ensure they reflect real-world scientific workflows.

Job details

Materials Science Coding Expert Position: Materials Science Coding Expert Type: Hourly Contract Compensation: $70/hour Location: Remote About the Opportunity Mercor is partnering with leading AI labs on a new benchmark for scientific computing and is seeking PhD and Master's-level scientists to author challenging, executable research problems for evaluating frontier AI models. In this role, you'll use your expertise in semiconductor materials and molecular modeling, combined with scientific programming skills, to create rigorous evaluation tasks that test whether advanced AI systems can solve complex research problems. Responsibilities Source original scientific material from published papers, Kaggle datasets, open-source repositories, or self-designed research scenarios. Develop scientifically rigorous prompts based on the selected research material. Author original, executable scientific computing problems focused on materials science. Build detailed grading criteria that define what constitutes a correct and high-quality solution. Ensure tasks accurately reflect real-world scientific computing and research workflows. Calibrate newly developed tasks against frontier AI models. Evaluate whether AI systems can successfully solve the authored problems. Refine tasks until they provide meaningful challenges for advanced models. Use coding and computational methods to create reproducible scientific evaluation tasks. Contribute to a high-quality benchmark for next-generation scientific AI. Required Qualifications PhD in Materials Science, Materials Engineering, Applied Physics, Chemistry, Chemical Engineering, or a closely related field. Demonstrated depth in both semiconductor materials and molecular modeling. Working proficiency in Python, R, or another relevant scientific-computing language. Strong understanding of scientific computing and computational research workflows. Comfortable working with Git/GitHub. Experience running code in Docker. Ability to work within a pull-request workflow and automated quality-check environment. Strong scientific writing and problem-formulation skills. Ability to independently develop rigorous research problems and grading criteria. Preferred Qualifications Publications in peer-reviewed scientific journals. Previous scientific software development experience. Research engineering experience. Experience developing computational models or simulations in materials science. Familiarity with open-source scientific repositories and research datasets. Experience creating reproducible computational research workflows. Compensation $70 per hour Remote hourly contract. 6-week engagement. Part-time commitment of 20+ hours per week. Immediate start. Eligibility Advanced degree in Materials Science, Materials Engineering, Applied Physics, Chemistry, Chemical Engineering, or a closely related discipline. Demonstrated expertise in semiconductor materials and molecular modeling. Candidates must have sufficient scientific programming experience to author and execute computational research tasks. Application Process Upload your resume and complete the application form. Participate in a 25-minute conversational interview covering your background, experience, and motivation. Await follow-up regarding next steps and onboarding. Complete onboarding and begin the six-week scientific computing benchmark engagement.

What you’ll do

Author and develop rigorous, executable scientific computing problems and grading criteria to evaluate frontier AI models in materials science. Source original research material and calibrate tasks to ensure they reflect real-world scientific workflows.

Requirements

Requires a PhD or Master's degree in Materials Science, Applied Physics, Chemistry, or a related field with expertise in semiconductor materials and molecular modeling. Proficiency in Python or R, Git, and Docker is essential for creating reproducible computational tasks.

Listed skills

• GitHub · Preferred
• Docker · Preferred
• Data analysis · Preferred
• Git · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Materials Science
• Molecular Modeling
• Semiconductor Materials
• Python
• R
• Scientific Computing
• Git
• GitHub
• Docker
• Scientific Writing
• Problem Formulation
• Computational Research
• Research Engineering
• Data Analysis
• Software Development
• Benchmark Development

Job areas

• Science & Research
• Engineering
• Technology
• Software
• Data & Analytics