Alignerr
Applied Physics
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Applied Physics
Applied Physics (AI Training)
About The Role
What if your mastery of quantum mechanics, electrodynamics, and thermodynamics could directly shape how AI understands the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models — exposing where they break the laws of physics and helping ensure they reason with the rigour of a trained scientist.
This is a fully remote, flexible contract role, built for researchers and academics who want high-impact work on their own schedule. No prior AI experience required — just deep domain expertise and an uncompromising eye for physical truth.
Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week
What You’ll Do
- Design Advanced Physics Problems — Craft challenging, open-ended problems at PhD qualifying exam level that demand:
- Multi-step logical reasoning
- Mathematical derivation
- Mastery of core physical principles
- Author Rigorous Solutions — Produce definitive, step-by-step "golden responses" with:
- Perfect physical constants
- Accurate unit conversions
- Airtight logical flow
- Audit AI Reasoning — Evaluate AI-generated simulations, proofs, and explanations for:
- Physical consistency
- Where models "hallucinate" physics that violates first principles
- Refine Model Behaviour — Provide structured, expert feedback to teach AI to respect constraints such as:
- Conservation laws
- Boundary conditions
- Dimensional analysis
- Cover Foundational Topics — Work across:
- Classical mechanics
- Electrodynamics
- Statistical mechanics
- Quantum mechanics
- Related research-level domains
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Who You Are
** Requirements**
- Holds a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery of core pillars:
- Classical Mechanics
- Electrodynamics
- Statistical Mechanics
- Quantum Mechanics
- Exceptional ability to articulate complex physical phenomena and mathematical derivations in clear, structured English
- Uncompromising precision with:
- Units
- Scientific notation
- Dimensional analysis
- Logical proof structure
- Self-motivated, reliable, and adept at independent work on task-based assignments
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** No prior AI or data annotation experience required.
Nice to Have
- Experience with:
- Data annotation
- Scientific dataset evaluation
- Quality assurance (QA) for research outputs
- Proficiency with computational tools such as:
- Python (NumPy/SciPy)
- MATLAB
- COMSOL
- Background in:
- Research-level problem design
- Academic instruction or scientific writing
- Familiarity with AI language models or large-scale model evaluation as an end user
Why Join Us
- Work on high-impact AI projects in collaboration with world-leading research labs
- Fully remote and flexible — work on your own schedule
- Enjoy freelance autonomy while contributing research-level work
- Contribute directly to ensuring AI systems reason about the physical world with scientific integrity
- Potential for ongoing work and contract extensions as new projects launch
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Jessica, London
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