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AbbVie’s mission is to discover and deliver innovative medicines 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, eye care, virology, women’s health and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.

Senior Scientist I/II, Machine Learning Bioinformatics - (REMOTE Optional)

Lake County, Illinois Req ID 2110893 Category Research and Development Division AbbVie

The Genomics Research Center (GRC) is a center of excellence for genetics and genomics that supports both Discovery and Development. The GRC plays an integral role towards our goal of developing world class genetics and genomics research, focusing on finding the right targets and helping us better understand not only human disease biology but also the behavior of and response to our drugs in clinical trials. Within the GRC, the Department of Bioinformatics is responsible for data analysis and provides analytical insight for both internal and external data. This involves the identification and characterization of underlying genetic, epigenetic, or genomic factors that are associated with disease diagnosis, prognosis and response (efficacy and safety) to drug treatment, identification of new targets, and interpretation of the impact of genetic and genomic evidence from population-based studies. We have an exciting opportunity for a Senior Bioinformatics Scientist, based in North Chicago IL, Cambridge, MA  or Remote. The candidate will work closely with computational biologists and research project teams in Immunology discovery to analyze genetics and multi-omics datasets to derive insights into immunological diseases, identify novel therapeutic targets and biomarkers specific to patient cohorts and Abbvie pipeline drugs.   

Key Responsibilities

  • Collaborate with research and bioinformatics scientists to conceive informatics analysis strategy leveraging advanced machine learning/AI algorithms to support discovery and pre-clinical studies.  Specific applications can be but not limited to single cell sequencing data integration and analysis, digital pathology and molecular data integration, etc.
  • Draft specific project analysis plans and execute them per project analysis needs leveraging publicly available algorithms and libraries and internal computing infrastructure.
  • Collaborate with systems engineers from Abbvie AI team to build necessary computational infrastructure and pipelines.
  • Identify relevant internal and external immunological datasets and knowledge resources. Propose and execute computational research leveraging these integrated datasets.
  • Be abreast with most current machine learning/AI analysis methodology and algorithms and introduce them in-house when appropriate.
  • Communicate analytical results verbally and in writing for scientific and technical audiences and journal publications.
Qualifications:

Position will be hired based on level of experience & education.

  • PhD in bioinformatics related quantitative sciences (such as computer science, applied mathematics, statistics, biomedical engineering) with biomedical data analysis experience.
  • 3+ years of project- based experience applying machine learning to knowledge graphs and other large- scale complex data is preferred.
  • Fluenct in Python or R with expertise in machine learning packages such as PyTorch, Tensorflow, and scikit-learn.
  • Ability to summarize analytical results, derive interpretation and recommend follow up actions to peer scientists.
  • Demonstrated ability to develop and execute custom computational and statistical analysis plans leveraging novel algorithms and relevant databases and statistical theory.
  • Prior working experience embedded within a biomedical research team.
  • Strong communication skills, innate scientific curiosity and collaborative team spirit.

Preferred Qualifications

  • Working experience in biopharma industry.
  • Working experience with Spark/Hadoop.
  • Fluent with architecting cloud-based pipelines, including data modeling, indexing, and ETL (experience with Redshift/BigQuery, Apache Beam, Spark)
  • Experience in single cell data analysis (scRNAseq, CITE/REAP-seq, CyTOF) on immune datasets.
  • Genomics and genetic data analysis (populational or disease centric) experience.
  • Collaborative experience with system engineers.
Significant Work Activities: N/A
Travel: No
Job Type: Experienced
Schedule: Full-time
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