Physics Research Expert (Solver)

Nextmark; United States; On-site; USD 90,000 - 160,000; Full time

Job summary

Nextmark is seeking a PhD-level physicist to guide AI training with rigorous physics-based input. You’ll solve advanced problems, develop models in Python/SymPy/Jupyter, and provide publication-quality explanations.

The role requires independent work, excellent communication, and being based in the US/UK/Canada with eligibility to work in the US. Prior AI-training experience is valued but not required; domain knowledge matters most.

Qualifications

• PhD in physics with active, ongoing research in targeted subfields.
• 2–5 representative publications (last 5 years) with arXiv/DOI links.
• Proficiency in mathematical modeling, derivations, and proofs at publication standards.
• Proficient in LaTeX, Python, SymPy, and Jupyter; strong written and verbal communication.
• Must be based in the US, UK, or Canada with ability to work in the US if required.

Responsibilities

• Contribute deep domain expertise in physics subfield for AI training inputs.
• Formulate, solve, and document advanced mathematical physics problems.
• Develop and validate computational models, simulations, and analyses using Python/SymPy/Jupyter.
• Produce publication-quality explanations and derivations with clear reasoning.
• Communicate complex concepts clearly with project coordinators and AI team.
• Work independently to address novel research problems with minimal supervision.
• Review and improve problem solutions for accuracy and clarity in AI training.

Skills

LaTeX

Python

SymPy

Jupyter

Academic writing

Independent work

Technical communication

Education

PhD in Physics

Tools

Python

SymPy

Jupyter

Job description

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.

Key Responsibilities

• Contribute deep domain expertise in your specialized physics subfield, providing authentic, up-to-date insights for AI training initiatives.
• Formulate, solve, and document advanced mathematical physics problems using rigorous methodologies.
• Develop and validate computational models, simulations, and analytical solutions leveraging Python, SymPy, and Jupyter environments.
• Produce high-quality, publication-level written explanations and derivations with clear, structured reasoning.
• Clearly communicate complex concepts and solutions through both written and verbal exchanges with project coordinators and the technical AI team.
• Work independently to navigate and resolve challenging, novel research problems aligned with the assigned subfield.
• Leverage your experience to review, critique, and improve problem solutions, ensuring accuracy and clarity for AI training.

Required Skills & Qualifications

• PhD (or senior PhD student) in physics with active, ongoing research in one or more targeted subfields: High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology/Astrophysics, Quantum Information, or Optical properties of materials.
• 2–5 representative publications (last 5 years) in the relevant subfield, with available arXiv/DOI links.
• Expertise in mathematical modeling, derivations, and system proofs at a publication-worthy standard.
• Proficient in LaTeX, Python, SymPy, and Jupyter (flag any skill gaps).
• Exceptional written and verbal communication skills—clarity, accuracy, and the ability to explain intricate concepts are essential.
• Demonstrated ability to work independently and execute research tasks with minimal supervision.
• Must be based in the US, UK, or Canada (rare exceptions for truly exceptional candidates).

Preferred Qualifications

• Experience in AI training or interdisciplinary computational research projects.
• Recognition as a thought leader, contributor, or reviewer in your physics subfield.