Associate Scientist, Post Doc Fellow- Computational Immunology

We are seeking a highly motivated Postdoctoral Research Fellow to join a cross-functional translational research team focused on understanding the cellular and tissue mechanisms underlying chronic immune-mediated inflammatory diseases. The successful candidate will leverage large-scale single-cell and spatial transcriptomics datasets from human tissue cohorts to identify disease-driving cellular programs, tissue microenvironments, and translational biomarkers. This position offers a unique opportunity to work at the interface of computational biology, immunology, spatial genomics, and translational medicine while contributing to high-impact research programs spanning multiple therapeutic areas.

The project aims to transform emerging multi-omics datasets into biological insights, biomarker hypotheses, disease-mechanism models, and translational strategies relevant to immune-mediated inflammatory diseases, including hidradenitis suppurativa (HS) and related disorders.

• Receive mentorship from experts across computational biology, immunology, translational medicine, and drug discovery.
• Publish first-author manuscripts in leading scientific journals.
• Present at major international scientific conferences.
• Develop expertise in cutting-edge single-cell, spatial, and multi-omics technologies.
• Build a strong interdisciplinary network across academia and industry.
• Gain experience translating complex biological datasets into actionable therapeutic insights.

The successful candidate will contribute to the development of comprehensive cellular and spatial atlases of chronic immune-mediated inflammatory diseases, generating insights into disease circuits, tissue microenvironments, biomarker biology, and translational mechanisms. The work is expected to result in multiple high-impact publications and presentations while providing foundational knowledge to support therapeutic discovery and development. This research will help advance our understanding of how cellular programs and tissue organization contribute to disease pathogenesis and therapeutic response, enabling more precise approaches to target discovery, biomarker identification, and patient stratification.

• Develop comprehensive single-cell transcriptomic references from diseased and comparator tissues.
• Identify disease-associated immune, epithelial, stromal, and vascular cell states.
• Harmonize and annotate cellular populations across cohorts and studies.
• Characterize molecular pathways and regulatory programs that drive disease heterogeneity.
• Define shared and disease-specific cellular mechanisms across inflammatory conditions.

• Analyze spatial transcriptomics datasets to localize disease-associated cell states within tissue architecture.
• Characterize cellular neighborhoods and multicellular interaction networks in situ.
• Identify tissue microenvironments associated with inflammation, remodeling, fibrosis, and disease progression.
• Develop computational frameworks for spatial niche discovery and tissue organization analysis.
• Integrate spatial and single-cell datasets to generate mechanistic hypotheses regarding disease biology.

• Evaluate target expression and pathway activity across cellular and spatial contexts.
• Identify biomarkers associated with disease biology, therapeutic response, and patient stratification.
• Characterize disease endotypes and molecular signatures linked to clinical heterogeneity.
• Integrate multimodal datasets to construct disease-mechanism and translational biology models.
• Generate hypotheses supporting therapeutic target evaluation and precision medicine approaches.

• Analyze large-scale single-cell RNA-seq, spatial transcriptomics, and related multi-omics datasets.
• Develop and implement computational methods for data integration, annotation, and interpretation.
• Apply advanced bioinformatics, statistical modeling, machine learning, and network biology approaches.
• Integrate transcriptomic, spatial, proteomic, and clinical data to generate biological insights.
• Collaborate closely with immunologists, translational scientists, clinicians, and computational researchers.
• Lead publication-quality analyses and prepare…