AbbVie's Quantitative Insights Lab needs to leverage innovative bioinformatic data analysis to generate actionable insights for its therapeutic areas by utilizing genetics and 'omics data at scale. The intern will play a vital role in creating and optimizing resources to advance the understanding of disease mechanisms through innovative data integration and representation techniques.
Requirements
- Proficient with statistical and programing languages (R, Python) and Linux environment
- Experience writing custom functions in R or python to statistically interrogate and visualize high dimensional biological datasets
- Demonstrated ability to execute custom computational analysis plans leveraging novel algorithms and relevant databases
- 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
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
Other
- 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
- Evidence of independent research capability including hypothesis development, experimental design and execution, data interpretation, and problem solving
- Very good communication skills demonstrated in inter-disciplinary teams.
- A self-motivated individual with a strong work ethic
