Internship Biostatistics Phd Internship information
See salary details
$11.06 - $12.74
2% of jobs
$12.74 - $14.42
4% of jobs
$16.11 is the 25th percentile. Wages below this are outliers.
$14.42 - $16.11
19% of jobs
$16.11 - $17.79
24% of jobs
The median wage is $17.89 / hr.
$17.79 - $19.47
17% of jobs
$20.48 is the 75th percentile. Wages above this are outliers.
$19.47 - $21.15
16% of jobs
$21.15 - $22.84
6% of jobs
$22.84 - $24.52
5% of jobs
$24.52 - $26.20
3% of jobs
$26.20 - $27.88
3% of jobs
$27.88 - $29.57
1% of jobs
How much do internship biostatistics phd internship jobs pay per hour?
As of Aug 17, 2026, the average hourly pay for internship biostatistics phd internship in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.
An Internship Biostatistics PhD Internship is a temporary position designed for PhD students in biostatistics or related fields to gain practical experience working on real-world data analysis projects, often within the pharmaceutical, biotech, or academic sectors. Interns apply statistical methods to clinical or biomedical data, collaborate with research teams, and develop skills essential for future careers in biostatistics. These internships typically last a few months and provide valuable exposure to industry practices, software, and research environments.
PhD biostatistics interns often contribute to real-world research projects, such as analyzing clinical trial data, developing or validating statistical models, and supporting the design of experimental studies. Interns usually collaborate with multidisciplinary teams that include statisticians, data scientists, and medical researchers, providing statistical expertise and insights. These projects may culminate in presentations or reports and often offer opportunities to publish or co-author scientific papers, enhancing both practical experience and academic credentials.
To thrive as a Biostatistics PhD Intern, you need a solid foundation in statistical theory, data analysis, and a strong background in mathematics or statistics, typically supported by ongoing PhD studies. Familiarity with statistical programming languages such as R, SAS, or Python, and experience with data management systems are commonly required. Strong problem-solving skills, attention to detail, and the ability to communicate complex statistical concepts clearly make candidates stand out. These competencies are critical for accurately analyzing biomedical data, supporting research projects, and effectively collaborating with interdisciplinary teams.
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