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Statistics Professor Jobs in Raleigh, NC (NOW HIRING)

micro1 AI

AI Training Specialist - Physics

Cary, NC · On-site +1

$80 - $150/hr

Physics Expert (Postdoc / Junior professor) Role Type: Contractor Location: Remote (US, Canada, UK ... Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum ...

NCSU

Temporary Research Technician

Raleigh, NC · On-site

$15.75 - $21.50/hr

... Professor to support the Agroecology Lab and the Agroecology Education Farm. The technician will assist in a variety of tasks aimed at data visualization and statistics related to the Agroecology ...

NCSU

CLAWS Fabrication Technician

Raleigh, NC

Hub leadership, Distinguished Professors John Muth and Fred Kish, are dedicated to the "lab to fab ... Statistical methods (e.g., DOE, GR&R) and tools (e.g., JMP, Minitab) Required License or ...

NCSU

CLAWS Electronics Test Engineer

Raleigh, NC

Hub leadership, Distinguished Professors John Muth and Fred Kish, are dedicated to the "lab to fab ... Leverage statistical methods to define test capabilities such as GR&R or MSA. * Oversee equipment ...

NCSU

Extension Corn Agronomist

Raleigh, NC · On-site

... Associate or Full Professor level. The successful candidate will have extension and research ... Familiarity with statistical analysis tools and software used in agricultural research. * Writing ...

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Showing results 21-39

All JobsStatistics Professor JobsStatistics Professor Jobs in Raleigh, NC

Statistics Professor information

See Raleigh, NC salary details

$10.7K

$79.6K

$98.2K

How much do statistics professor jobs pay per year?

As of Aug 19, 2026, the average yearly pay for statistics professor in Raleigh, NC is $79,586.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,300.00 and $97,200.00 per year, depending on experience, location, and employer.

What is a statistics professor?

A Statistics Professor is an academic professional who teaches, researches, and applies statistical methods in various fields. They typically work at universities or colleges, instructing students in probability, data analysis, and statistical theory. Their responsibilities include designing courses, conducting research, publishing findings, and mentoring students. Some professors also collaborate with industries or government agencies to solve real-world data problems.

What are the typical daily responsibilities of a statistics professor?

Statistics Professors typically divide their time between teaching undergraduate and graduate courses, conducting research, publishing academic papers, and advising students. They often develop and update course materials, hold office hours to support student learning, and participate in departmental meetings or academic committees. Collaboration with other faculty members and supervising student research projects are also common aspects of the role. This mix of teaching, research, and service helps maintain a dynamic and intellectually engaging work environment.

What are the key skills and qualifications needed to thrive in the statistics professor position, and why are they important?

To thrive as a Statistics Professor, you need a deep understanding of statistical theory, applied statistics, and a PhD in statistics or a closely related field. Proficiency with statistical software such as R, SAS, SPSS, or Python, and experience publishing peer-reviewed research are highly valued. Excellent communication, mentoring, and classroom management skills help build rapport with students and facilitate effective learning. These skills are essential for delivering complex material clearly, conducting research, and mentoring the next generation of statisticians.

How much do statistics professors make?

Statistics professors' salaries vary based on experience, education, and institution type, but typically range from $70,000 to over $150,000 annually. Professors at research universities or with tenure tend to earn higher salaries, and additional income may come from research grants or consulting. Salaries are also influenced by geographic location and academic rank.

How to become a statistics professor?

To become a statistics professor, one typically needs to earn a doctoral degree in statistics, mathematics, or a related field, and develop expertise through research and publications. Academic positions also require teaching experience and a strong record of scholarly work, often supplemented by proficiency in statistical software and research methods.

What does a statistics professor do?

A statistics professor teaches courses in statistical methods, data analysis, and probability at the college or university level. They conduct research in statistics or related fields, publish findings, and may advise students on academic and research projects. They often use statistical software and require strong analytical and communication skills.

What are popular job titles related to Statistics Professor jobs in Raleigh, NC?

For Statistics Professor jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Statistics Professor jobs in Raleigh, NC look for?

The top searched job categories for Statistics Professor jobs in Raleigh, NC are:

Statistics Professor jobs near you
Infographic showing various Statistics Professor job openings in Raleigh, NC as of August 2026, with employment types broken down into 80% Full Time, 18% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $79,586 per year, or $38.3 per hour.

AI Training Specialist - Physics

micro1 AI

Cary, NC • On-site, Remote

$80 - $150/hr

Part-time

Posted 16 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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