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Research Scientist Optimization Jobs in Raleigh, NC

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

AI Training Specialist - Physics

Cary, NC · On-site +1

$80 - $150/hr

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

... research platforms, high-throughput laboratories, or remotely accessible scientific infrastructure. * Experience integrating laboratory robotics with artificial intelligence, optimization algorithms ...

Assisting in the creation and optimization of automated data curation systems. * Integrating peak ... Bachelor's degree in physical sciences, mathematical sciences, or a related STEM field. * 2+ years ...

Assisting in the creation and optimization of automated data curation systems. * Integrating peak ... Bachelor's degree in physical sciences, mathematical sciences, or a related STEM field. * 2+ years ...

Showing results 21-40

Research Scientist Optimization information

See Raleigh, NC salary details

$49.1K

$126.5K

$169.1K

How much do research scientist optimization jobs pay per year?

As of Sep 15, 2026, the average yearly pay for research scientist optimization in Raleigh, NC is $126,484.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $168,200.00 per year, depending on experience, location, and employer.

What does a research scientist in optimization do?

A Research Scientist in Optimization specializes in developing and applying mathematical techniques to improve processes, systems, or algorithms. Their work often involves formulating optimization problems, designing solutions, and collaborating with engineers or data scientists to implement and test their models. These scientists may work in various industries, such as technology, logistics, finance, or manufacturing, to help organizations make better decisions, save resources, or improve performance. Their daily tasks include conducting experiments, analyzing large datasets, and publishing findings in scientific journals.

What are the key skills and qualifications needed to thrive as a research scientist in optimization?

To excel as a Research Scientist in Optimization, you need a strong background in mathematics, computer science, and optimization theory, often supported by a PhD in a related field. Familiarity with programming languages like Python or MATLAB, optimization libraries (e.g., Gurobi, CPLEX), and experience with data analysis tools are typically required. Critical thinking, creativity, and strong communication skills help in formulating novel approaches and presenting complex findings clearly. These skills drive the development of efficient algorithms and solutions, advancing research impact and innovation in the field.

What types of projects and collaborations can a research scientist in optimization expect to be involved in?

As a Research Scientist specializing in Optimization, you can expect to work on projects that involve developing and improving algorithms to solve complex real-world problems in areas such as logistics, supply chain, or machine learning. Collaboration is common, often involving cross-functional teams with data scientists, software engineers, and domain experts to implement and test optimization solutions. You may also contribute to academic publications, attend conferences, and sometimes mentor junior researchers, all while staying current with the latest advancements in optimization techniques.

What is the difference between Research Scientist Optimization vs Data Scientist?

AspectResearch Scientist OptimizationData Scientist
Required CredentialsMaster's or PhD in Operations Research, Mathematics, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, R&D departments, academiaBusiness analytics, tech companies, consulting firms
Industry UsageOptimization problems, algorithm development, mathematical modelingData analysis, predictive modeling, data visualization

Research Scientist Optimization focuses on developing mathematical models and algorithms to solve complex optimization problems, often in research or academic settings. Data Scientists analyze large datasets to extract insights and build predictive models for business decisions. While both roles require strong analytical skills, Research Scientist Optimization emphasizes mathematical and algorithmic development, whereas Data Scientists focus on data analysis and interpretation.

What job categories do people searching Research Scientist Optimization jobs in Raleigh, NC look for?

The top searched job categories for Research Scientist Optimization jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Research Scientist Optimization jobs?

Cities near Raleigh, NC with the most Research Scientist Optimization job openings:

Infographic showing various Research Scientist Optimization job openings in Raleigh, NC as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 12% Part Time, and 5% Contract. Highlights an 72% Physical, 4% Hybrid, and 24% Remote job distribution, with an average salary of $126,484 per year, or $60.8 per hour.

Senior Scientific Reviewer - Physics

Durham, NC • On-site, Remote

micro1 AI
Software Development • 11 - 50 employees

$80 - $150/hr

Part-time

Re-posted 13 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.