Postdoc, Immunology R&D: Data Science for Drug Discovery

jj; Pennsylvania; On-site; USD 79,000 - 128,000; Full time

Job summary

Johnson & Johnson Innovative Medicine is recruiting a Postdoctoral Scholar to join the Data Sciences group to identify and evaluate drug targets in immunology, supporting alignment of priorities with the Immunology therapeutic area.

The role involves analyzing large-scale clinical, genetic, omics, and cell phenotype data to advance the drug discovery pipeline, with opportunities to apply ML, network analyses, and cross-functional collaboration across JJ teams.

Qualifications

• PhD in a quantitative field with strong biological basis (Bioinformatics/Computational Biology/Systems Biology).
• Completed PhD program.
• Experience with multi-omic data (bulk and single-cell).
• Knowledge of gene/pathway ontology and network analysis.
• Proficiency in programming and collaboration with scientists.

Responsibilities

• Construct an analytic framework integrating perturbation, ontology, and cellular phenotyping with omics data.
• Apply ML methods to link targets to disease states and predict mechanisms.
• Provide expertise in modeling multimodal data to predict pathway activity and interactions.
• Use statistical modeling and AI/ML to identify targets and biomarkers.
• Translate computational findings to support experimental validation.

Skills

PhD in Quantitative Field

Multi-omics Data

Programming & Computational Skills

Independent & Collaborative

Communication & Leadership

Education

PhD in Bioinformatics/Computational Biology/Related Field

Tools

Network Analysis

RNA-seq

Single-cell Analysis

ML/AI Methods

Job description

Johnson & Johnson Innovative Medicine is recruiting a Postdoctoral Scholar to join the Data Sciences group to identify and evaluate drug targets in immunology, supporting alignment of priorities with the Immunology therapeutic area.

The role involves analyzing large-scale clinical, genetic, omics, and cell phenotype data to advance the drug discovery pipeline, with opportunities to apply ML, network analyses, and cross-functional collaboration across JJ teams.