Condensed Matter Physicist AI Training

Apply advanced expertise in magnetic materials and condensed matter physics to help train next-generation AI systems through high-quality scientific analysis and real-world input.

• Analyze and interpret magnetic structure factors using propagation-vector methods and advanced symmetry concepts.
• Identify and classify antiferromagnetic, ferromagnetic, and related magnetic phases from theoretical and experimental data, including neutron diffraction results.
• Curate and validate magnetic space group assignments using MAGNDATA and BNS notation conventions.
• Evaluate birefringence and magneto-optic Kerr effect signatures, connecting optical behavior to underlying magnetic structures.

• Advanced academic background in condensed matter physics, preferably a PhD or equivalent research experience, with a specialization in magnetism or a related field.
• Proficiency in magnetic structure factor calculations, propagation-vector analysis, and symmetry-based phase identification.
• Experience classifying magnetic space groups, including hands‑on familiarity with MAGNDATA and BNS notation.
• Strong knowledge of neutron scattering techniques for determining magnetic structures.
• Ability to relate experimental signatures such as birefringence and magneto-optic Kerr effect results to their physical mechanisms.
• No prior AI experience is required.

Remote, contract engagement.

$80 to $160 per hour.