Computational Structural Biology information
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$14.66 - $19.71
4% of jobs
$19.71 - $24.76
6% of jobs
$24.76 - $29.81
11% of jobs
$30.65 is the 25th percentile. Wages below this are outliers.
$29.81 - $34.86
19% of jobs
The median wage is $37.13 / hr.
$34.86 - $39.90
21% of jobs
$44.95 is the 75th percentile. Wages above this are outliers.
$39.90 - $44.95
14% of jobs
$55.05 - $60.10
5% of jobs
$60.10 - $65.14
4% of jobs
$65.14 - $70.19
3% of jobs
How much do computational structural biology jobs pay per hour?
As of Aug 17, 2026, the average hourly pay for computational structural biology in the United States is $41.13, according to ZipRecruiter salary data. Most workers in this role earn between $30.05 and $48.56 per hour, depending on experience, location, and employer.
Computational structural biology is a field that uses computer-based methods and simulations to study the three-dimensional structures of biological molecules, such as proteins and nucleic acids. Researchers use computational tools to predict molecular structures, analyze their dynamics, and understand how they interact with other biomolecules. This approach complements experimental techniques like X-ray crystallography and cryo-electron microscopy, helping scientists gain insights into biological function and design drugs or therapies. The field integrates knowledge from biology, chemistry, physics, and computer science.
To thrive as a Computational Structural Biologist, you need a solid background in structural biology, molecular modeling, and bioinformatics, typically supported by a PhD or relevant advanced degree. Proficiency in programming languages (such as Python or R), molecular visualization tools (like PyMOL or Chimera), and experience with structural databases are commonly required. Strong analytical thinking, collaboration, and communication skills help you interpret complex data and work effectively within multidisciplinary teams. These competencies are crucial for advancing scientific understanding and developing novel therapeutics in the field of structural biology.
One common challenge is effectively communicating complex computational findings to experimental colleagues who may not be familiar with certain modeling techniques. Additionally, aligning computational predictions with experimental data can require iterative discussions to ensure that models are biologically relevant and experimentally testable. Successful collaboration often relies on building mutual understanding of each team's methodologies and limitations, which fosters productive interdisciplinary research.
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