Senior Scientist, Multiomics Perturbation

Johnson & Johnson Innovative Medicine is seeking a Senior Scientist to join the Data, Data Science & AI (DDSAI) organization, based in Spain. In this role, you will lead the design, execution, and application of advanced computational models to integrate multi-modal perturbation data and human omics datasets for target/pathway nomination.

You will drive the development of predictive frameworks for disease state reversal, nominate synergistic target combinations, and perform in silico target deconvolution to inform portfolio decisions in immune-mediated diseases.

Key Responsibilities

• Lead the design, optimization, and validation of human-omics driven perturbation prediction models integrating genetic and/or chemical perturbation data, including bulk/single-cell transcriptomics, proteomics, cytokine profiles, and other cellular screening data to predict disease-reversal phenotypes in disease models.
• Develop advanced computational methods to perform target deconvolution, identify target combinations and pathway perturbation that most effectively reverse pathogenic activities.
• Build human-omics-based phenotype scoring frameworks to quantify perturbation efficacy, validated across internal datasets and public databases.
• Collaborate closely with therapeutic discovery, disease biology and preclinical safety leads to ensure computational predictions align with experimental design and biological context.
• Provide technical leadership — set analytical roadmaps, define milestones, quantify success metrics, and ensure reproducibility and scalability across workflows.

Required Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Systems Biology, Biomedical Engineering, Computer Science, Statistics, Electrical Engineering, Data Science, Artificial Intelligence, or a related quantitative field.
• 2+ years postdoctoral or industry experience in large-scale multi-omics data analysis (e.g., genomics, transcriptomics, proteomics and single cell omics), preferably in therapeutic discovery or translational research.
• Proven expertise and hands-on experience in developing AI/ML models for biological datasets, including deep learning, generative modelling, representation learning and transformer-based methods; ideally with experience of in silico modelling of cellular response to genetic or chemical perturbations.
• Experience working with multimodal biological datasets, including perturbation screens, transcriptomics, single-cell and spatial omics, proteomics, and genetic or epigenomic data.
• Experience in phenotype scoring development and evaluation, multi-omics integration between human and in vitro models.
• Advanced skills in high-performance/cloud computing, reproducible pipeline development (e.g. Nextflow), and workflow optimization.

Preferred Qualifications

• Experience in in vitro perturbation data analysis (e.g. Perturb-seq) and chemical-target mapping.
• Knowledge of public omics databases.
• Background in systems biology and network/pathway analysis and integrative data harmonization across platforms.
• Familiarity with immune-mediated disease biology, especially fibroblast pathobiology.
• Experience in AI skills and agent development.

The anticipated base pay range for this position is €55,400.00 - €87,860.00, plus an annual bonus. You will have the flexibility to work at our Spanish sites (Madrid or Cornellà de Llobregat, Barcelona) with global team integration.