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PlotFuture / Careers / Mathematical Science Teachers, Postsecondary

Mathematical Science Teachers, Postsecondary

Also known as: Adjunct Mathematics Instructor, Assistant Professor, Associate Professor, Instructor, Math Teacher
median $79,94010-yr demand +2.3%AI exposure 43/100typical entry Doctoral or professional degree
Mathematical Science Teachers, Postsecondary is mid-paying, AI barely touches it so far, and demand is steady.

The full pay distribution

Not one number — the spread from the bottom 10% to the top 10% of filed salaries.

Where it pays the most

Median salary by metro — the bar in amber is the U.S. median for comparison.

How pay grows with experience

From entry to expert, by reported wage level.

How exposed is it to AI?

Two things matter: how much AI is actually used in the role today (right), and how much it could automate in theory (up). AI is already widely used here.
Each faint dot is another occupation. The amber dot is Mathematical Science Teachers, Postsecondary — its position tells you whether the disruption is here yet or still over the horizon.
used today 43/100 automatable in theory 54/100 archetype The Epicenter

If AI does come for this job — where could you go?

Adjacent careers ranked by how much safer + how much more they pay, and the skill gap to get there. Click any to see its full breakdown.

Which majors lead here

College paths that commonly feed this career — see each one's full outcomes.
Teacher Education And Professional Development, Specific Subject Areas
CIP 13.13
see major →
Biomathematics, Bioinformatics, And Computational Biology
CIP 26.11
see major →
Mathematics
CIP 27.01
see major →
Applied Mathematics
CIP 27.03
see major →
Statistics
CIP 27.05
see major →
Applied Statistics
CIP 27.06
see major →
Mathematics And Statistics, Other
CIP 27.99
see major →
Mathematics And Computer Science
CIP 30.08
see major →
Mathematics And Atmospheric/Oceanic Science
CIP 30.50
see major →
Philosophy
CIP 38.01
see major →
Management Sciences And Quantitative Methods
CIP 52.13
see major →
How this is built. Median pay and the full distribution come from filed U.S. wage data (BLS OEWS + DOL/LCA filings); AI exposure blends O*NET task content with model-based automation potential; escape routes are computed from skill overlap between occupations, then ranked by how much safer + better-paid the move is. This joins real distributions and projects them forward — it needs the real distributions and the skill graph, not a guess. Figures describe group medians and trends, not any one person's outcome.