Applied Physics
Posted Today by Alignerr
Negotiable
Undetermined
Remote
Cambridge, England, United Kingdom
Summary: The role of Applied Physicist focuses on leveraging expertise in physics to evaluate and enhance AI models' understanding of physical principles. Candidates will design complex physics problems, audit AI reasoning, and provide structured feedback to improve model accuracy. This fully remote position is ideal for PhD-level researchers seeking flexible, intellectually stimulating work. No prior AI experience is necessary, but a strong analytical mindset and deep domain knowledge are essential.
Key Responsibilities:
- Design Advanced Physics Problems — Craft PhD qualifying exam-level problems spanning quantum mechanics, electrodynamics, classical mechanics, and thermodynamics that demand multi-step logical reasoning and mathematical derivation
- Author Gold-Standard Solutions — Develop rigorous, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is unimpeachable
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Provide Structured Feedback — Coach AI systems to reason correctly about boundary conditions, conservation laws, and real-world physical constraints
- Document Failure Modes — Systematically record how and where AI reasoning breaks down so that research teams can build better, more physically grounded models
Key Skills:
- Holds a PhD (completed or near-completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional analytical writing skills — you can explain a complex derivation in clear, structured prose without losing rigor
- Uncompromising precision when it comes to units, scientific notation, dimensional analysis, and the logical flow of a proof
- Self-motivated and reliable when working independently and asynchronously
- No prior AI or data annotation experience required
- Experience with data annotation, scientific dataset evaluation, or quality assurance for research outputs (nice to have)
- Proficiency with computational tools such as MATLAB, COMSOL, Python (NumPy/SciPy), or similar (nice to have)
- Background in experimental or computational physics research (nice to have)
- Familiarity with AI or machine learning concepts as an end user or researcher (nice to have)
Salary (Rate): £32.00/hr
City: Cambridge
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: Other
Applied Physics (AI Training)
About The Role
What if your expertise in 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 the gaps in their physical reasoning and helping ensure they never violate the fundamental laws of the universe. This is a fully remote, flexible contract role built for researchers and academics who want to do meaningful, intellectually stimulating work on their own schedule. No prior AI experience required — just deep domain mastery and a rigorous, analytical mind.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Physics Problems — Craft PhD qualifying exam-level problems spanning quantum mechanics, electrodynamics, classical mechanics, and thermodynamics that demand multi-step logical reasoning and mathematical derivation
- Author Gold-Standard Solutions — Develop rigorous, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is unimpeachable
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Provide Structured Feedback — Coach AI systems to reason correctly about boundary conditions, conservation laws, and real-world physical constraints
- Document Failure Modes — Systematically record how and where AI reasoning breaks down so that research teams can build better, more physically grounded models
Who You Are
- Holds a PhD (completed or near-completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional analytical writing skills — you can explain a complex derivation in clear, structured prose without losing rigor
- Uncompromising precision when it comes to units, scientific notation, dimensional analysis, and the logical flow of a proof
- Self-motivated and reliable when working independently and asynchronously
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, scientific dataset evaluation, or quality assurance for research outputs
- Proficiency with computational tools such as MATLAB, COMSOL, Python (NumPy/SciPy), or similar
- Background in experimental or computational physics research
- Familiarity with AI or machine learning concepts as an end user or researcher
Why Join Us
- Work on high-impact AI projects in collaboration with the world's leading AI research labs
- Fully remote and flexible — work when and where it suits you, on your own schedule
- Freelance autonomy with the intellectual depth of meaningful, research-level work
- Gain direct exposure to how frontier large language models are trained and evaluated
- Contribute to AI development that could shape how technology understands the physical world for decades to come
- Potential for ongoing work and contract extension as new projects launch