Postdoctoral Fellow, Genetic Mechanisms & Target Discovery in Autoimmune Disease

Biohub is a 501(c)(3) biomedical research organization building the first large-scale scientific initiative combining frontier AI with frontier biology to solve disease. We build the technology to help scientists around the world use AI-powered biology to study how cells operate, organize, and work as part of systems to understand why disease happens and how to correct it. With our compute capacity, AI research and engineering, and state-of-the-art technology for measuring, imaging, and programming biology, we are enabling scientists worldwide to use AI-powered biology to advance our understanding of human health. The Team Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer’s, and Parkinson’s. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here . Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity The Laboratory of Immunogenomics at Biohub in NY (www.mahatlab.com) studies the non-coding regulatory genome to understand and address immune dysfunction in diseases like cancer, autoimmune disorders, and aging. We focus on enhancers—non-coding, highly cell-type-specific transcriptional regulatory elements—and their role in shaping immune responses. We develop and utilize genomic technologies, including bulk and single-cell nascent RNA sequencing, genome editing, immune engineering, and CRISPR-based functional screens in patient biopsies, organoid systems, and mouse models. Through computational analysis integrating machine learning and AI, we map enhancer–gene networks and identify disease-driving elements. Our goal is to advance enhancer-guided precision genomic medicine for diseases involving immune dysfunction. We seek a Postdoctoral Fellow to dissect the non-coding genomic mechanisms underlying common autoimmune diseases (e.g., Type 1 Diabetes, Systemic Lupus Erythematosus, Celiac Disease, etc.). Over 80% of autoimmune disease-associated variants map to non-coding regions across numerous susceptibility loci, yet their target genes, relevant cell types, and molecular mechanisms remain largely unknown. This project aims to identify causal regulatory variants, map their cell-type-specific effects, and link genetic variation to immune dysfunction and disease phenotypes. What You'll Do Variant Prioritization and Fine-Mapping Apply Bayesian fine-mapping (FINEMAP, SuSiE) to GWAS loci, integrating multi-ancestry data. Overlay variants with nascent RNA sequencing, open chromatin regions, histone modifications, and transcription factor motifs across relevant immune and target cell types. Cell-Type-Specific Mechanism Mapping Perform single-cell eQTL analysis in disease-relevant cell types (e.g., T cell subsets, B cell subsets, monocytes, or target-tissue cells) from patients. Map stimulus-dependent effects under key inflammatory or activating conditions (e.g., IFN, TLR agonists, TCR/BCR stimulation). Use promoter-capture Hi-C or similar methods to identify variant target genes through long-range chromatin interactions. Functional Validation Execute MPRAs (Massively Parallel Reporter Assays) testing allele-specific enha ... (truncated, view full listing at source)