Biochemistry at University of Richmond

University of Richmond, VA · Private nonprofit · Bachelor's Degree · Biochemistry, Biophysics and Molecular Biology
25 /100
DegreeOutlook Score (Base Case)
25
Optimistic
25
Base Case
28
Pessimistic
Earnings $34,796/yr (-8% vs median)
AI Risk High (45% exposed)
Job Market Large (45,200 openings/yr)
ROI 1.8x earnings multiple
Ranked #123 of 136 Biochemistry & Biophysics and Molecular Biology programs

How AI Changes the Outlook

Three scenarios based on how aggressively AI disrupts the career paths available to Biochemistry graduates.

Optimistic
No Disruption
Base Case
Gradual AI
Pessimistic
Aggressive AI
10-Year Earnings $439K $443K $428K
Earnings Multiple 1.8x 1.8x 1.7x
Probability of Field Employment 58% 53% 40%
DegreeOutlook Score 25 25 28

10-Year Earnings Projection

*Year 1 uses actual reported earnings. Scenarios diverge as AI impact compounds over time.

4-Year Tuition (Sticker)
$250,400
4-Year Net Price (After Aid)
$133,668
47% less than sticker · See by income
Median Debt at Graduation
$23,346
8.1 months of Year 1 earnings

About University of Richmond

University of Richmond admits 23% of applicants, placing it among selective institutions, a smaller institution with 3,002 students in University of Richmond, VA. Financial aid reduces the effective four-year cost to $133,668 — 47% less than the list price.

See all programs and financial aid at University of Richmond →

Top Career Paths

Natural sciences managers $161,180/yr
Biochemists and biophysicists $103,650/yr
Medical scientists, except epidemiologists $100,590/yr
View all 8 career paths with salary ranges and AI risk →

Compare & Explore

Biochemistry at Other Schools

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Frequently Asked Questions

How does University of Richmond's Biochemistry program score?
This program scores 25/100 — on the lower end for Biochemistry. Prospective students should carefully weigh costs against likely earnings.
How vulnerable is Biochemistry to AI automation?
AI won't 'replace' Biochemistry careers outright, but it is likely to reduce the number of job openings. We model 45% task exposure, which compresses field employment probability in our scenarios.
Scores use College Scorecard earnings, BLS employment projections, and AI task-exposure research. See full methodology →