Condensed Matter Physicist for AI Training

Role Overview

Apply your condensed matter physics expertise to research work involving magnetic space groups, neutron scattering, BNS notation, and the physical signatures of magnetic order. Your analysis will help train next-generation AI systems through high-quality, real-world scientific input. Prior AI experience is not required.

Key Responsibilities

• Analyze and interpret magnetic structure factors using propagation-vector methods and advanced symmetry concepts.
• Identify and classify antiferromagnetic, ferromagnetic, and related magnetic phases using theoretical data, experimental data, and neutron diffraction results.
• Curate and validate magnetic space group assignments against established resources, including MAGNDATA, while ensuring alignment with BNS notation conventions.
• Evaluate birefringence and magneto-optic Kerr effect signatures in selected materials, linking optical behavior to the underlying magnetic structure.
• Contribute domain expertise that improves how AI systems learn, reason, and perform.

Qualifications

• 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 identifying and classifying magnetic space groups, including hands-on familiarity with MAGNDATA and BNS notation.
• Strong knowledge of neutron scattering methods for magnetic structure determination.
• Ability to connect experimental signatures, including birefringence and magneto-optic Kerr effect results, to their underlying physical mechanisms.

Work Terms

• Remote contract engagement.

Compensation

• $80 to $160 per hour.