ironquill.tech/board

$ cat jobs/physics-expert-postdoc-junior-professor-micro1-5dbe6340316d.json

Physics Expert (Postdoc / Junior professor)

micro1·UK·United Kingdom·junior
python
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Role Title: Physics Expert (Postdoc / Junior professor) Role Type: Contractor Location: Remote (US, Canada, UK focused) micro1 is engaging Physics Experts (Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the science and technology sector. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work Critically evaluate and review physics solutions, mathematical derivations, and theoretical arguments generated by researchers or AI platforms. Detect errors, unjustified steps, missing assumptions, dimensional inconsistencies, and weaknesses in logic or methodology. Delineate between substantive scientific issues and stylistic or cosmetic matters, providing technically precise written feedback. Articulate and document the reasoning behind any identified flaws, ensuring actionable guidance for improvement. Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the argument. Utilize LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate. Deliver structured feedback designed to support iterative enhancement of submitted work and project outcomes. Preferred Qualifications PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum Information, or Optical Materials). Experience as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist. Recent (last ~5 years) representative publications in the relevant subfield, with arXiv or DOI links. Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical model

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