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Arrowhead Pharmaceuticals · 8 hours ago

Summer Intern, Statistical Genetics & Human Biobanks

San Diego, CA

Internship

Onsite

Intern

$27/hr - $27/hr

Arrowhead Pharmaceuticals is a clinical stage biopharmaceutical company focused on developing innovative drugs for diseases with a genetic basis. The Statistical Genetics & Human Biobanks Intern will support Translational Genetics research by developing AI-augmented workflows to identify disease-relevant genes for RNAi target discovery, collaborating with scientists to generate high-confidence hypotheses.

BiotechnologyHealth CareNanotechnologyPharmaceutical

Comp. & Benefits

No H1B

Responsibilities

Support analysis of large-scale genetic and biomedical datasets to help identify disease-relevant signals

Assist in developing and applying analytical and AI-enabled workflows for data integration, interpretation, and reporting

Contribute to evidence synthesis and data summarization to support research and target evaluation efforts

Help assess consistency and robustness of findings across multiple datasets or sources

Prepare clear summaries, visualizations, or reports to communicate results to the project team

Present updates and findings during team meetings and participate in scientific discussions

Collaborate with scientists and computational team members on research projects and special initiatives

Qualification

Statistical GeneticsPythonRBioinformaticsFunctional GenomicsPopulation GeneticsData AnalysisCommunication SkillsCollaboration Skills

Required

Currently pursuing a PhD in Statistical Genetics, Human Genetics, Computational Biology, Bioinformatics, Biostatistics, or a closely related field

Hands-on experience analyzing data from at least one major human biobank

Proficiency in Python and/or R for statistical genetics and data analysis workflows

Familiarity with GWAS summary statistics, rare variant interpretation (pLoF/GoF), and functional genomics datasets such as eQTL and pQTL

Strong understanding of population genetics, genetic architecture, and variant-to-gene mapping

Ability to translate genetic association evidence into actionable therapeutic hypotheses

Excellent verbal and written communication skills and ability to collaborate in a cross-functional research environment

Preferred

Proficiency with statistical genetics and functional genomics tools such as REGENIE, SAIGE, TWAS frameworks, Mendelian randomization packages, and colocalization methods

Demonstrated ability to interpret pLoF/GoF variants and integrate eQTL/pQTL data with GWAS findings to identify causal genes and pathways

Experience developing AI- or LLM-assisted analytics for evidence synthesis, automation, or variant-to-gene mapping

Strong interest in translational genetics, RNAi therapeutics, and data-driven target discovery