Postdoctoral and Research Specialist Positions in Microbiome, Immunology, and Computational Biology
The Translational Microbiome & Immune Tolerance Laboratory at the University of Maryland School of Medicine, Center for Advanced Microbiome Research and Innovation (CAMRI) within the Institute of Genome Sciences (IGS) is recruiting postdoctoral fellows, PhD students, and research specialists to join our interdisciplinary team studying the gut microbiome’s role in immune tolerance development. Our lab integrates multi-omics, experimental models, and clinical cohorts to investigate molecular mechanisms by which gut microbial metabolism shapes host immunity.
Prospective PhD and MD/PhD students should apply through the Molecular Microbiology & Immunology and Molecular Medicine Graduate Programs of the University of Maryland, Baltimore. We also welcome rotation students, visiting researchers or PhD students from other institutions — please contact Dr. Ozcam directly via email.
The successful postdoctoral candidate will generate, analyze, and integrate multi-omics microbiome datasets, including shotgun metagenomics, 16S rRNA sequencing, single-cell transcriptomics, and proteomics/metabolomics. The overarching goal of the study is to investigate how early-life diet shapes the functional capacity of the gut microbiome and how these microbial functions are associated with the development of childhood allergic diseases. The candidate will develop machine learning–based biomarker prediction models to identify microbiome-derived signatures associated with allergy risk and immune tolerance outcomes.
Computational Biology & Data Integration Position
Focus: Multi-omics microbiome analysis, single-cell transcriptomics, machine learning based biomarker prediction
Key areas:
-Shotgun Metagenomic , and 16S rRNA sequencing analysis
-Single-cell RNA-seq and proteomic/metabolomic data integration
-Machine learning and AI applications in microbiome data
-Clinical metadata harmonization across cohorts
-Integration of clinical and multi-omic data to uncover microbiome–host relationships
-Experience with Python/R and cloud computing preferred
Ideal candidate: A computational biologist or bioinformatician with strong programming skills and a keen interest in applying AI to biological systems, particularly in the context of clinical datasets and microbiome-driven disease mechanisms.
What We Offer
-Access to clinical samples from well-characterized pediatric cohorts
-Collaborative environment across CAMRI and IGS
-Mentorship in academic career development
-Cutting-edge tools in multi-omics and host-microbe systems biology
To apply, please send a CV to mozcam@som.umaryland.edu.