Semiconductor Material Science (Masters/PhDs)

Alignerr Corp.; Australia; Remote; AUD 96,000 - 179,000; Full time

Job summary

Alignerr Corp. is seeking a Semiconductor Material Science Expert (AI Training) for a remote hourly contract. The role targets Masters or PhD holders who can shape AI systems' reasoning in physical sciences.

Flexible 10–40 hours/week, remote work, no prior AI experience required—your scientific expertise matters. You will collaborate asynchronously with AI researchers, applying semiconductor materials and advanced modeling to craft rigorous problem statements and evaluate AI outputs for accuracy

Qualifications

• Master's or PhD in Material Science or related field.
• Deep expertise in semiconductor materials or molecular modeling.
• Proficiency in Python or MATLAB for research, simulation, or data analysis.
• Excellent written and verbal communication with attention to detail.

Responsibilities

• Develop, solve, and review advanced material science problems with real-world relevance.
• Apply expertise in semiconductor materials and molecular modeling to design complex problems.
• Evaluate AI-generated scientific reasoning for accuracy and depth.
• Collaborate asynchronously with AI researchers and domain experts to improve model performance.
• Maintain scientific rigor and clear, high-quality deliverables.

Skills

Semiconductor materials

Molecular modeling

Python

MATLAB

Scientific communication

Education

Master's or PhD in Material Science or related field

Tools

Python

MATLAB

Job description

Semiconductor Material Science Expert (AI Training)

About The Role

What if your deep expertise in semiconductor materials or molecular modeling could directly shape how the world's most advanced AI systems reason about physical science? We're looking for Material Science specialists — Masters and PhD holders — to work alongside leading AI research teams, helping build AI models that can think, reason, and problem-solve at an expert level.

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. No prior AI experience required — your scientific expertise is what matters.

• 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 scientific relevance
• Apply your expertise in semiconductor materials, molecular modeling, or related fields to design complex, rigorous problem statements
• Evaluate AI-generated scientific reasoning and outputs for accuracy, depth, and technical correctness
• Collaborate asynchronously with AI researchers and fellow domain experts to sharpen AI model performance
• Ensure scientific rigor, clarity, and depth across all deliverables — your standards set the bar

Who You Are

• Holds a Master's or PhD in Material Science, or a closely related field
• Deep expertise in semiconductor materials, molecular modeling, or adjacent research areas
• Comfortable coding in Python or MATLAB for research, simulation, or data analysis
• Exceptionally clear communicator — both in writing and verbally — with a sharp eye for detail
• Self-directed, reliable, and comfortable working independently in an asynchronous environment
• Based in the U.S., Canada, U.K., Australia, or New Zealand

Nice to Have

• Prior experience with data annotation, data quality evaluation, or AI evaluation workflows
• Background in computational materials science, thin-film technology, or device physics
• Familiarity with AI tools or large language model outputs as an end user
• Experience reviewing or editing scientific literature or technical documentation

Why Join Us

• Work on frontier AI projects in partnership with the world's leading AI research labs
• Fully remote and asynchronous — work when and where it works for you
• Freelance autonomy with the substance of genuinely challenging, expert-level work
• Make a direct, lasting impact on how AI understands and reasons about materials science
• Potential for ongoing work and contract extension as new projects launch