Alignerr
Material Science Specialist (Masters/PhDs)

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Material Science Specialist (Masters/PhDs)
Material Science Specialist (AI Training)
About The Role
What if your deep expertise in materials science could directly shape how AI reasons through some of the most complex problems in modern science? We're looking for Materials Science specialists—Masters and PhD holders—to help train and evaluate cutting-edge AI models working on semiconductor materials, molecular modeling, and advanced materials challenges.
This is a fully remote, flexible contract role built for researchers and domain experts who want to put their hard-earned knowledge to work on something genuinely new. No prior AI experience needed—your scientific depth 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 materials science problems with real-world scientific relevance
- Apply your expertise in semiconductor materials, molecular modeling, or related disciplines to craft complex, high-quality problem statements
- Evaluate AI-generated reasoning and outputs for scientific accuracy, rigor, and depth
- Collaborate asynchronously with AI researchers and fellow domain experts to push the boundaries of what AI can understand in your field
- Ensure clarity, precision, and scientific integrity across all deliverables
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Who You Are
Core Requirements
- Master’s or PhD in Materials 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 or analytical purposes
- Exceptionally clear written communicator—you can explain complex science with precision and purpose
- Detail-oriented with a rigorous, methodical approach to problem-solving
- No prior AI or data annotation experience required—full training support is provided


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Nice-to-Have
- Prior experience with data annotation, data quality evaluation, or AI model review
- Background in computational materials science or materials informatics
- Experience reviewing or writing technical research documentation
- Familiarity with AI tools or scientific evaluation workflows
Why Join Us
- Work on frontier AI projects alongside world-leading research labs
- Fully remote and asynchronous—work when and where it suits you
- Freelance autonomy with the structure of meaningful, intellectually stimulating work
- Apply your advanced degree to problems that directly influence how AI understands materials science
- Potential for ongoing work and contract extension as new projects launch
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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