Postdoctoral Fellow in Bioinformatics

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 for Genome Sciences (IGS) is recruiting a postdoctoral fellow to join our interdisciplinary team studying the gut microbiome's role in immune tolerance development. Our lab integrates multi-omics microbiome analyses, microbial genetics, experimental models, and clinical cohorts to investigate mechanisms by which early-life gut microbial metabolism shapes host immunity.

The successful 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 project 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.

Qualifications:

Preferred Skills

• Analysis of shotgun metagenomics sequencing and metabolomics data
• Integration of single-cell RNA-seq with proteomic and metabolomic datasets
• Application of machine learning and AI approaches to microbiome data
• Harmonization and management of clinical metadata across cohorts
• Integration of clinical and multi-omic datasets to uncover microbiome–host interactions
• Strong statistical skills in Python and/or R
• Experience with cloud computing and high-performance computing environments

Ideal Candidate Profile

We are seeking a computational biologist, biostatistician or bioinformatician with strong quantitative and programming expertise and a demonstrated interest in applying AI and machine learning approaches to complex biological systems.

What We Offer

• Access to clinical samples from well-characterized pediatric cohorts.
• Collaborative environment across CAMRI and IGS.
• Access to Maryland Genomics Resources and Trainings.
• Cutting-edge tools in multi-omics and host-microbe interactions.

To apply, please send a CV to mozcam@som.umaryland.edu.