Condensed Matter Physicist for AI Model Training

Provide expert condensed matter and magnetism analysis to a research program focused on magnetic space groups, neutron scattering, BNS notation, and observable signatures of magnetic order. Your domain expertise will be used to generate high quality, real-world content that trains and evaluates next generation AI models. No prior experience in AI is required.

• Analyze and interpret magnetic structure factors using propagation-vector methodologies and symmetry concepts in condensed matter physics.
• Identify and classify magnetic phases, including AFM and FM types, using theoretical calculations and experimental data, such as neutron diffraction results.
• Curate and validate magnetic space group assignments with reference to established datasets, including MAGNDATA, and ensure correct correspondence with BNS notation.
• Evaluate optical and magneto-optical signatures, such as birefringence and the magneto-optic Kerr effect (MOKE), and relate these observations to underlying magnetic structures.
• Produce clear, domain-accurate inputs and validations that improve how AI systems learn and reason about magnetic materials.

• Advanced academic background, PhD or equivalent research experience, in condensed matter physics with a focus on magnetism or a closely related field.
• Demonstrated proficiency in magnetic structure factor calculations and propagation-vector analysis.
• Experience with symmetry-based phase identification and classification of magnetic space groups.
• Hands-on familiarity with MAGNDATA and BNS notation for magnetic space groups.
• Strong knowledge of neutron scattering techniques as applied to magnetic structure determination.
• Ability to connect experimental signatures, including birefringence and MOKE, to underlying physical mechanisms.

• Role type, contractor.
• Location, remote.
• No prior AI experience required; emphasis is on subject matter expertise in physics and magnetism.

Pay range, $80 to $160 per hour.

• Candidates must be able to work as independent contractors under remote engagement terms.