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# Condensed Matter Physicist for AI Model Training

- **Company:** Careerjet All Rights Reserved
- **Location:** Washington, DC, United States
- **Salary:** $166,400.0 - $332,800.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Word, Microsoft Excel, Artificial Intelligence, Experimental Data, Machine Learning, Microsoft PowerPoint, Extensible Markup Language (XML)
- **Published:** August 4, 2026
- **Apply:** https://www.careerjet.com/job/register/usf3329d233a87cb357976216929b588bb

## About the Role

* Advanced academic background, such as a PhD or equivalent research experience, in condensed matter physics or a closely related field with a focus on magnetism.
 * Demonstrated proficiency in magnetic structure factor calculations and propagation vector analysis.
 * Hands-on experience classifying magnetic space groups, with familiarity using MAGNDATA and applying BNS notation.
 * Strong knowledge of neutron scattering methods for determining magnetic structures.
 * Experience connecting experimental signatures, for example birefringence and MOKE, to physical mechanisms behind magnetic order.

Work Terms

 * Engagement type, independent contractor., * No prior AI experience required; applicants must have the domain expertise described above.
 * Candidates should be able to work as independent contractors and participate in any required vetting or screening processes.

## Description

You will apply specialist condensed matter and magnetism expertise to analyze magnetic order, interpret neutron scattering and optical signatures, and validate magnetic space group assignments. Your contributions will be used to train and evaluate next generation AI systems, providing high quality, domain-grounded data and judgments. Prior experience in AI is not required; deep domain knowledge is the priority. Key Responsibilities

 * Analyze and interpret magnetic structure factors using propagation vector methods and symmetry-based approaches.
 * Identify and classify magnetic phases, including antiferromagnetic and ferromagnetic order, from theoretical and experimental data.
 * Process and correlate neutron diffraction and other scattering results to determine magnetic structures.
 * Curate and validate magnetic space group assignments, referencing established datasets such as MAGNDATA, and ensure consistency with BNS notation conventions.
 * Evaluate optical and magneto-optic signatures, including birefringence and magneto-optic Kerr effect, and link these observations to underlying magnetic structures and mechanisms.
 * Provide clear, precise explanations and examples that can be converted into training or evaluation material for AI systems., * Work may involve reviewing experimental data, performing analyses, and producing annotated explanations suitable for model training., Role Overview Use advanced Excel, Word, and PowerPoint skills to design realistic business scenarios, create and evaluate Office Open XML documents, and provide detailed, profess…
 + 1 day ago


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