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The differences between computational biologists and resource biologists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 6-8 years to become both a computational biologist and a resource biologist. Additionally, a computational biologist has an average salary of $61,449, which is higher than the $55,582 average annual salary of a resource biologist.
The top three skills for a computational biologist include python, machine learning and next-generation sequencing. The most important skills for a resource biologist are GIS, water quality, and GPS.
| Computational Biologist | Resource Biologist | |
| Yearly salary | $61,449 | $55,582 |
| Hourly rate | $29.54 | $26.72 |
| Growth rate | 17% | 1% |
| Number of jobs | 12,839 | 8,041 |
| Job satisfaction | - | - |
| Most common degree | Bachelor's Degree, 53% | Bachelor's Degree, 90% |
| Average age | 40 | 40 |
| Years of experience | 8 | 8 |
Computational biologists and resource biologists have different pay scales, as shown below.
| Computational Biologist | Resource Biologist | |
| Average salary | $61,449 | $55,582 |
| Salary range | Between $38,000 And $99,000 | Between $35,000 And $87,000 |
| Highest paying City | San Francisco, CA | - |
| Highest paying state | Alaska | - |
| Best paying company | - | |
| Best paying industry | Health Care | - |
There are a few differences between a computational biologist and a resource biologist in terms of educational background:
| Computational Biologist | Resource Biologist | |
| Most common degree | Bachelor's Degree, 53% | Bachelor's Degree, 90% |
| Most common major | Biology | Biology |
| Most common college | Harvard University | University of California, Berkeley |
Here are the differences between computational biologists' and resource biologists' demographics:
| Computational Biologist | Resource Biologist | |
| Average age | 40 | 40 |
| Gender ratio | Male, 80.2% Female, 19.8% | Male, 58.8% Female, 41.2% |
| Race ratio | Black or African American, 2.7% Unknown, 5.1% Hispanic or Latino, 7.4% Asian, 17.0% White, 67.2% American Indian and Alaska Native, 0.6% | Black or African American, 2.3% Unknown, 4.9% Hispanic or Latino, 6.3% Asian, 11.1% White, 74.7% American Indian and Alaska Native, 0.6% |
| LGBT Percentage | 10% | 10% |