2026 Quantitative Insights Lab Intern (PhD)

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

This internship opportunity is in the Quantitative Insights Lab of the QM&G organization which plays a key role in using innovative bioinformatic data analysis to generate actionable insights for AbbVie’s therapeutic areas by leveraging genetics and ‘omics data at scale. Under the supervision of senior scientists, the intern will compile results from large internal and external databases of functional genomic perturbation data, including CRISPR screens and Perturb-seq datasets to connect genes to molecular functions associated with diseases across Therapeutic Areas (TAs). The intern will have the opportunity to participate in cross-functional team efforts to develop a knowledge graph framework that can be used to extract meaningful insights.  

Importance: The intern will play a vital role in the creation and optimization of resources to advance the understanding of disease mechanisms through innovative data integration and representation techniques. 

Key Responsibilities: 

• Ingest existing internal and external compilations of perturbation data into a common knowledge graph 
• Integrate with other data sources in AbbVie knowledge graphs such as genetic associations and pathways to draw connections between genes, gene perturbations, and disease mechanisms.  
• Assess predictive performance of functional screens to identify outcomes of interest such as known drug mechanisms 

Qualifications

Minimum Requirements 

• Currently enrolled in university, pursuing PhD in Computational Biology, Bioinformatics, Statistical Genetics or related field 
• Must be enrolled in university for at least one semester following the internship 
• Proficient with statistical and