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Engineering Teachers, Postsecondary vs Materials Scientists

Side-by-side · O*NET · BLS · AI-exposure research · Anthropic Economic Index

A factual, source-backed comparison of Engineering Teachers, Postsecondary and Materials Scientists on the dimensions both occupations carry. Every figure is a position within an independent published dataset — not a verdict on which job is better, safer, or more “future-proof.”

Engineering Teachers, Postsecondary Materials Scientists
Median pay · BLS OEWS
$106,120
$104,160
Employment · BLS OEWS
39,910
8,330
AI exposure (percentile) · task overlap, not automation
95th pct
78th pct

At a glance

Dimension Engineering Teachers, Postsecondary Materials Scientists
Median pay $106,120 $104,160
Employment 39,910 8,330
Employment outlook (2024–34) · BLS projection Growing fast (+8.1%) About average (+4.9%)
Annual openings · BLS projection 4,100 600
Typical education · O*NET Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree). Most of these occupations require a four-year bachelor's degree, but some do not.
AI exposure · published exposure studies High · 95th pct High · 78th pct
Global GenAI gradient · ILO ISCO-08 · via crosswalk 70th pct · 37% of tasks 62nd pct · 34% of tasks
Observed AI use · Anthropic Economic Index Augmentation-leaning (67.0%) Augmentation-leaning (49.0%)
Mostly remote-capable · Dingel–Neiman Yes No

Pay and employment are BLS OEWS estimates; outlook and openings are BLS 2024–2034 projections; AI exposure and observed-use figures come from separate research and reflect exposure and usage, not predictions that either job will disappear. Compare like with like.

Skills

Shared: Engineering and Technology, Design, Computers and Electronics, Mathematics, Oral Expression, English Language, Speech Clarity, Physics, Speaking, Written Comprehension, Reading Comprehension, Active Listening, Oral Comprehension, Writing, Mathematics, Critical Thinking, Written Expression, Deductive Reasoning, Inductive Reasoning, Judgment and Decision Making, Information Ordering, Category Flexibility, Mathematical Reasoning, Near Vision, Speech Recognition, Active Learning, Science, Mechanical, Monitoring, Problem Sensitivity, Number Facility, Complex Problem Solving, Fluency of Ideas, Originality, Chemistry.

Specific to Engineering Teachers, Postsecondary

  • Learning Strategies
  • Instructing
  • Education and Training
  • Administration and Management
  • Coordination

Specific to Materials Scientists

  • Production and Processing
  • Flexibility of Closure
  • Persuasion
  • Operations Analysis
  • Systems Evaluation

Knowledge, skills & abilities O*NET rates as important for each occupation. “Shared” are common to both; the columns list what is distinctive to each (top by the order O*NET surfaces).

Tools & technology

Shared: Object or component oriented development software , Word processing software , Web platform development software , Spreadsheet software , Office suite software , Electronic mail software , Presentation software , Analytical or scientific software , Internet browser software .

Specific to Engineering Teachers, Postsecondary

Specific to Materials Scientists

Full profiles

This page is a summary. See the complete source-backed profile for Engineering Teachers, Postsecondary or Materials Scientists — tasks, the full skill graph, tools, work context, preparation, wages by percentile, industries, AI exposure and the AI work map.

More comparisons

Related occupations you can place side by side on the same sourced scale.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Engineering Teachers, Postsecondary vs Materials Scientists." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/compare/engineering-teachers-postsecondary-vs-materials-scientists

APA

Singulariki. (2026). Engineering Teachers, Postsecondary vs Materials Scientists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/compare/engineering-teachers-postsecondary-vs-materials-scientists

BibTeX 
@misc{singulariki-engineering-teachers-postsecondary-vs-materials-scientists,
  title  = {Engineering Teachers, Postsecondary vs Materials Scientists},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/compare/engineering-teachers-postsecondary-vs-materials-scientists}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.