Retrieve cleaned and harmonized historical nonclinical toxicology control-group data using SQL
Develop and implement statistical analyses to characterize trends in chemical pathology measurements
Create reusable data pipelines and code-based workflows (R or Python) for retrospective analyses
Compare preclinical control data with published clinical pooled placebo data
Collaborate with cross-functional teams including nonclinical drug safety, veterinary pathology, and translational medicine
Present research findings in group meetings and prepare a final scientific presentation
Potentially contribute to publication of the project results
Requirements
Must be a full-time student currently enrolled in a Masters/PhD program in Biostatistics, Bioinformatics, Computational Biology, Engineering, Pharmaceutical Sciences, Toxicology, or related quantitative life science fields
Must have a strong background in statistics and quantitative bio-focused research, ideally as demonstrated by a publication or course project
Must be proficient in coding with R or Python for data analysis, especially data visualization tools
Must have an aptitude for thinking critically and creatively to overcome technical challenges
Must possess excellent verbal and written communication skills
Must have the ability to work independently and collaboratively in a fast-paced environment
Must be enrolled full-time in the Fall Semester at an accredited university/college after the internship
Must be able to complete a 10-12 consecutive week internship between May and August
Benefits
Professional development opportunities
Internship program
Networking events
Opportunities to participate in special events/programs for interns
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