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Mathematical Modeling Postdoc Jobs in Virginia (NOW HIRING)

micro1 AI

AI Training Specialist - Physics

Richmond, VA · On-site +1

$80 - $150/hr

Physics Expert (Postdoc / Junior professor) Role Type: Contractor Location: Remote (US, Canada, UK ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

AI Training Specialist - Physics

Newport News, VA · On-site +1

$80 - $150/hr

Physics Expert (Postdoc / Junior professor) Role Type: Contractor Location: Remote (US, Canada, UK ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

Research Consultant - Physics AI

Richmond, VA · Remote

$80 - $140/hr

Role Title: Physics Expert (PhD / Postdoc) Role Type: Contractor. Location: Remote micro1 is ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

Research Consultant - Physics AI

Suffolk, VA · Remote

$80 - $140/hr

Role Title: Physics Expert (PhD / Postdoc) Role Type: Contractor. Location: Remote micro1 is ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

Research Consultant - Physics AI

Roanoke, VA · Remote

$80 - $140/hr

Role Title: Physics Expert (PhD / Postdoc) Role Type: Contractor. Location: Remote micro1 is ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

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Mathematical Modeling Postdoc information

What is the difference between Mathematical Modeling Postdoc vs Data Scientist?

AspectMathematical Modeling PostdocData Scientist
Required CredentialsPhD in Mathematics, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; PhD preferred
Work EnvironmentAcademic research institutions, universities, research labsCorporate, tech companies, startups, or consulting firms
Industry UsageResearch projects, academic publications, grant-funded studiesBusiness analytics, product development, data-driven decision making
Common Search & ComparisonYesYes

While both roles involve analytical skills and data handling, Mathematical Modeling Postdocs focus on academic research and developing theoretical models, whereas Data Scientists apply data analysis techniques to solve practical business problems. The choice depends on whether you prefer research-oriented work or industry applications.

What does a mathematical modeling postdoc do?

A Mathematical Modeling Postdoc conducts advanced research using mathematical techniques to analyze and solve complex real-world problems in fields such as biology, engineering, physics, or social sciences. They typically develop and apply mathematical models, run simulations, analyze data, and interpret results to support scientific or industrial projects. Postdocs in this role often collaborate with interdisciplinary teams, publish research findings, and may also assist in mentoring students or contributing to grant proposals.

What are some common challenges faced by mathematical modeling postdocs when transitioning from academic research to collaborative industry projects?

Mathematical Modeling Postdocs often encounter challenges when moving from academic research to industry settings, particularly in adapting to faster-paced timelines and working within interdisciplinary teams. In industry, projects may require quick prototyping and the ability to communicate complex mathematical concepts to non-experts, such as engineers or business stakeholders. Building effective collaborations and aligning research goals with organizational objectives can also be a significant adjustment. However, these challenges provide valuable experience and broaden career prospects in both academia and industry.

What are the key skills and qualifications needed to thrive as a mathematical modeling postdoc?

A Mathematical Modeling Postdoc requires an advanced degree (typically a PhD) in mathematics, applied mathematics, or a related quantitative field, along with strong analytical and problem-solving abilities. Expertise with programming languages such as Python, MATLAB, or R, and experience with simulation software or computational tools, are commonly expected. Strong communication, collaboration, and critical thinking skills help in presenting findings and working effectively within research teams. These competencies are vital for developing robust models, interpreting complex data, and contributing to innovative research outcomes.

What are popular job titles related to Mathematical Modeling Postdoc jobs in Virginia?

For Mathematical Modeling Postdoc jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Mathematical Modeling Postdoc jobs in Virginia look for?

The top searched job categories for Mathematical Modeling Postdoc jobs in Virginia are:

What cities in Virginia are hiring for Mathematical Modeling Postdoc jobs?

Cities in Virginia with the most Mathematical Modeling Postdoc job openings:

Mathematical Modeling Postdoc jobs near you
Infographic showing various Mathematical Modeling Postdoc job openings in Virginia as of August 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 95% In-person, 2% Hybrid, and 3% Remote job distribution.

Physics Content Evaluator (LaTeX/Python)

micro1 AI

Norfolk, VA • On-site, Remote

$80 - $150/hr

Part-time

Posted 12 days ago

Job description

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

  1. Critically evaluate and review physics solutions, mathematical derivations, and theoretical arguments generated by researchers or AI platforms.
  2. Detect errors, unjustified steps, missing assumptions, dimensional inconsistencies, and weaknesses in logic or methodology.
  3. Delineate between substantive scientific issues and stylistic or cosmetic matters, providing technically precise written feedback.
  4. Articulate and document the reasoning behind any identified flaws, ensuring actionable guidance for improvement.
  5. Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the argument.
  6. Utilize LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate.
  7. Deliver structured feedback designed to support iterative enhancement of submitted work and project outcomes.


Preferred Qualifications

  1. 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).
  2. Experience as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist.
  3. Recent (last ~5 years) representative publications in the relevant subfield, with arXiv or DOI links.
  4. Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical modeling and computational validation.
  5. Demonstrated skill in reviewing the work of others—through peer review, supervision, dissertation committees, or group seminars.
  6. Exceptional written communication skills with the ability to convey nuanced, constructive feedback with technical rigor.
  7. Reliable access to high-speed internet and a computer suitable for rigorous technical work.

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