2026 Quantitative Insights Lab Intern (PhD)

Role Summary

2026 Quantitative Insights Lab Intern (PhD)

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

• Required: Currently enrolled in university, pursuing PhD in Computational Biology, Bioinformatics, Statistical Genetics or related field
• Required: Must be enrolled in university for at least one semester following the internship
• Required: Proficient with statistical and programming languages (R, Python) and Linux environment
• Required: Experience writing custom functions in R or Python to statistically interrogate and visualize high dimensional biological datasets
• Required: Demonstrated ability to execute custom computational analysis plans leveraging novel algorithms and relevant databases
• Required: Evidence of independent research capability including hypothesis development, experimental design and execution, data interpretation, and problem solving
• Required: Very good communication skills demonstrated in inter-disciplinary teams
• Required: A self-motivated individual with a strong work ethic

Preferred Qualifications

• Expected graduation date between December 2026 ‚Äì June 2027
• Experience processing and analyzing imaging data, single cell RNA-seq, CRISPR screens or other similar NGS/genomic data
• Experience with knowledge graph tools such as neo4j
• Experience with database management using SQL or other tools
• Experience with AWS cloud computing