Semiconductor Material Science (Masters/PhDs)

Job summary

Develop, solve, and review advanced materials science problems, applying expertise in semiconductor materials, molecular modeling, and related fields. Evaluate AI-generated scientific reasoning for accuracy and technical rigor, and collaborate asynchronously with researchers and domain experts to improve model performance.

Job details

Semiconductor Material Science Expert (AI Training) About The Role What if your deep expertise in semiconductor materials or molecular modeling could directly shape how AI reasons through some of the most complex problems in modern science? We're looking for Material Science specialists — Masters and PhD holders — to help train and evaluate cutting-edge AI models by crafting, solving, and reviewing advanced technical problems grounded in real-world science. This is a fully remote, flexible contract role built for researchers and domain experts who want to do meaningful, high-impact work on their own schedule. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Develop, solve, and critically review advanced material science problems with real-world relevance Apply your expertise in semiconductor materials, molecular modeling, or related areas to design rigorous, complex problem statements Evaluate AI-generated scientific reasoning for accuracy, depth, and technical correctness Collaborate asynchronously with AI researchers and fellow domain experts to strengthen model performance Ensure scientific rigor, clarity, and precision across every deliverable Work independently on task-based assignments — fully on your own schedule Who You Are Master's or PhD in Material Science, or a closely related discipline Strong expertise in semiconductor materials, molecular modeling, or adjacent technical fields Comfortable coding in Python or MATLAB for research or technical applications Exceptionally detail-oriented with strong written communication skills in English Self-motivated and reliable when working independently without supervision Currently based in the U.S., Canada, U.K., Australia, or New Zealand Nice to Have Prior experience with data annotation, data labeling, or AI evaluation workflows Background in industry or academic research with published or applied work Familiarity with computational materials science or simulation tools Experience explaining complex scientific concepts clearly and concisely Why Join Us Work on frontier AI projects alongside the world's leading research labs Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, task-based work Make a direct, tangible impact on how AI understands advanced scientific domains Potential for ongoing work and contract extension as new projects launch Training and onboarding support provided — no prior AI experience necessary

What you’ll do

Develop, solve, and review advanced materials science problems, applying expertise in semiconductor materials, molecular modeling, and related fields. Evaluate AI-generated scientific reasoning for accuracy and technical rigor, and collaborate asynchronously with researchers and domain experts to improve model performance.

Requirements

A master's or PhD in materials science or a closely related discipline is required, along with strong expertise in semiconductor materials, molecular modeling, or an adjacent field. Candidates should be comfortable using Python or MATLAB, communicate clearly in English, work independently, and be based in the United States, Canada, the United Kingdom, Australia, or New Zealand.

Benefits

• Flexible Schedule
• Fully Remote Work
• Freelance Autonomy
• Training And Onboarding Support
• Potential For Ongoing Work And Contract Extension

Listed skills

• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Semiconductor Materials
• Materials Science
• Molecular Modeling
• Python
• MATLAB
• Computational Materials Science
• Scientific Problem Design
• Scientific Reasoning Evaluation
• Technical Review
• AI Model Evaluation
• Data Annotation
• Data Labeling
• Scientific Writing
• Research

Job areas

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

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