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PlotFuture / Careers / Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary

Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary

Also known as: Assistant Professor, Associate Professor, Astronomy Professor, Atmospheric Sciences Professor, Geology Professor
median $103,17010-yr demand +2.6%AI exposure 4/100typical entry Doctoral or professional degree
Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary is well paid, 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.

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). Partially affected.
Each faint dot is another occupation. The amber dot is Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary — its position tells you whether the disruption is here yet or still over the horizon.
used today 4/100 automatable in theory 48/100 archetype The Hybrid Zone

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 →
Climate Science
CIP 30.35
see major →
Earth Systems Science
CIP 30.38
see major →
Environmental Geosciences
CIP 30.41
see major →
Mathematics And Atmospheric/Oceanic Science
CIP 30.50
see major →
Astronomy And Astrophysics
CIP 40.02
see major →
Atmospheric Sciences And Meteorology
CIP 40.04
see major →
Geological And Earth Sciences/Geosciences
CIP 40.06
see major →
Physics And Astronomy
CIP 40.11
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.