Material Science Specialist (Masters/PhDs)
Posted Today by Alignerr
Negotiable
Undetermined
Remote
London, England, United Kingdom
Summary: The Material Science Specialist role focuses on leveraging expertise in materials science to enhance AI's understanding of semiconductors and molecular structures. This fully remote position is designed for Masters and PhD level researchers to collaborate with AI teams, developing and reviewing complex scientific problems. No prior AI experience is required, emphasizing the importance of scientific knowledge. The role offers flexible hours ranging from 10 to 40 hours per week.
Key Responsibilities:
- Develop, solve, and critically review advanced materials science problems with real-world scientific relevance.
- Apply expertise in semiconductor materials, molecular modeling, or related domains to design complex, rigorous problem sets.
- Collaborate asynchronously with AI researchers and fellow domain experts to improve AI model reasoning in materials science.
- Evaluate the scientific accuracy, clarity, and depth of AI-generated content and outputs.
- Ensure the highest standards of scientific rigor across all deliverables.
Key Skills:
- Master's or PhD in Materials Science or a closely related field.
- Deep expertise in semiconductor materials, molecular modeling, or adjacent areas.
- Proficient in Python or MATLAB for research or technical applications.
- Exceptionally clear written communicator.
- Detail-oriented, self-motivated, and comfortable working independently in an asynchronous environment.
- Based in the U.S., Canada, U.K., Australia, or New Zealand.
Salary (Rate): £75.00/hr
City: London
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Material Science Specialist (AI Training)
About The Role
What if your deep expertise in materials science could directly shape how AI reasons about semiconductors, molecular structures, and the physical world? We're looking for Materials Science specialists — Masters and PhD level — to work alongside leading AI research teams and help train the next generation of scientific AI models. This is a fully remote, flexible contract role built for researchers and domain experts who want to put their knowledge to work in a high-impact, cutting-edge environment. 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 domains to design complex, rigorous problem sets
- Collaborate asynchronously with AI researchers and fellow domain experts to improve AI model reasoning in materials science
- Evaluate the scientific accuracy, clarity, and depth of AI-generated content and outputs
- Ensure the highest standards of scientific rigor across all deliverables
Who You Are
- Master's or PhD in Materials Science or a closely related field
- Deep expertise in semiconductor materials, molecular modeling, or adjacent areas
- Proficient in Python or MATLAB for research or technical applications
- Exceptionally clear written communicator — you can explain complex concepts with precision
- Detail-oriented, self-motivated, 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 training workflows
- Background in computational materials science, density functional theory, or related simulation methods
- Experience reviewing or producing technical documentation, research papers, or scientific assessments
Why Join Us
- Work on frontier AI projects alongside the world's leading AI research labs
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with the structure and consistency of meaningful, task-based work
- Apply your advanced scientific training to a domain that is actively shaping the future of technology
- Potential for ongoing work and contract extension as new projects launch