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Alignerr

Applied Physics Specialist

City of Edinburgh
$40 – $80/hr
Posted about 6 hours ago
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Applied Physics Specialist (AI Training)

About The Role

What if your years of graduate-level physics training could directly influence how AI reasons about the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their understanding of quantum mechanics, thermodynamics, electrodynamics, and more.

This is a fully remote, flexible contract role. No AI background needed — just deep domain expertise and the precision of a researcher who knows when something violates first principles.

Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week

What You'll Do

  • Design PhD-level problems — Craft advanced, open-ended physics problems requiring multi-step logical reasoning, mathematical derivation, and mastery of core physical principles
  • Author ground-truth solutions — Write rigorous, step-by-step "golden responses" where every constant, unit conversion, and logical step is airtight
  • Audit AI reasoning — Evaluate AI-generated solutions and proofs for physical consistency, identifying where models "hallucinate" physics that violates first principles
  • Refine model behaviour — Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints
  • Work independently and asynchronously — fully on your own schedule

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Who You Are

  • PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field
  • Deep mastery of the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
  • Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured prose
  • Uncompromising eye for detail — units, scientific notation, and the logical flow of a proof matter to you
  • Self-motivated and consistent when working independently
  • No prior AI or data annotation experience required

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Nice to Have

  • Experience with data annotation, scientific dataset evaluation, or academic benchmarking
  • Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
  • Background in research, academia, or applied engineering environments
  • Familiarity with AI tools or language model outputs as an end user

Why Join Us

  • Work on high-impact AI projects alongside the world's leading AI research labs
  • Fully remote and flexible — work when and where it suits you
  • Freelance autonomy with the structure of meaningful, intellectually rigorous work
  • Gain direct exposure to how frontier AI models are trained and evaluated
  • Contribute to ensuring that the next generation of AI systems genuinely understands the physical world
  • Potential for ongoing work and contract extension as new projects launch
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Skills

Applied Physics
Quantum Mechanics
Thermodynamics
Electrodynamics
Classical Mechanics
Statistical Mechanics
Mathematical Derivation
Logical Reasoning
Scientific Notation
Python
NumPy
SciPy
MATLAB
COMSOL
Data Annotation
Research

Location

City of Edinburgh, Scotland, United Kingdom

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