Postdoctoral Fellow, Microbiome-Host Immune System Interactions – Gerber Lab

The Gerber Lab ( is a multidisciplinary group at Brigham and Women’s Hospital/Harvard Medical School that develops novel computational models and high-throughput experimental systems to understand the role of the microbiota in human diseases, and applies these findings to develop new diagnostic tests and therapies. The director of the lab, Dr. Georg Gerber, MD, PhD, MPH, uses his unique expertise, combining advanced machine learning method development, medical microbiology, and human pathology, to leverage cutting-edge technologies to tackle scientifically and clinically important problems.

We are looking for an exceptional researcher who will play a major role in a new initiative in the lab to investigate systematically how commensal microorganisms interact with the host immune system. Although host-bacterial interactions have been extensively characterized for some pathogens, much less is known about how commensal bacteria in the microbiome interact with us. The lab will use both experimental systems (e.g., gnotobiotic animals and cell culture) and computational approaches to study various aspects of immune host system-microbiome interactions, including influence on infection/inflammation and immune repertoire development/diversity.

The successful candidate will be highly motivated and creative, taking a lead role in experimental design, execution of experiments, and interpretation of results. This position is a fantastic opportunity for an individual with strong experimental skills to learn about and apply computational techniques, enriched by extensive collaborations with top computational researchers.


  • PhD in Immunology, Microbiology, or related discipline.
  • Excellent publication track record.
  • Proficiency in cell and molecular techniques including cell culture, flow cytometry, qPCR, and ELISA assays.
  • Proficiency in mouse studies including animal handling, blood collection, necropsy and cell isolation.
  • Superior communication skills and ability to work on multidisciplinary teams.
  • Experience in cellular immunology, including immune cell proliferation is highly desirable.
  • Experience in microbiology, including culture of anaerobic bacteria is highly desirable.
  • Experience with next-generation sequencing library preparation and data analysis is highly desirable.

Environment:  the Gerber Lab is located in the Division of Computational Pathology (, which Dr. Gerber heads, at Brigham and Women’s Hospital (BWH) at Harvard Medical School (HMS), and the Massachusetts Host-Microbiome Center (MHMC) (, which Dr. Gerber co-directs. BWH, an HMS affiliated teaching hospital is adjacent to the HMS main quad and is the second largest non-university recipient of NIH research funding. The Division is situated within the BWH Department of Pathology, which houses over 40+ established investigators, 50+ postdoctoral research fellows, and 100+ research support staff. The MHMC has extensive facilities to support microbiome research, including the largest not-for-profit gnotobiotic mouse facility in New England, a microbiology unit with advanced anaerobic culturing systems, and a molecular unit with next generation sequencers and robotic liquid handlers. BWH is part of the greater Longwood Medical Area in Boston, a rich, stimulating environment conducive to intellectual development and research collaborations, which includes HMS, Harvard School of Public Health and Boston Children’s Hospital.

To apply: email a single PDF including cover letter, CV, brief research statement and a list of at least three references to Dr. Georg Gerber ( In your CV, indicate whether you are a U.S. citizen/permanent resident or visa holder (and list visa type). Incomplete applications will be considered non-responsive and unfortunately cannot be considered.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Harris H. Wang, PhD Columbia University-“Spatial metagenomics, culturomics, and engineering of human and environmental microbiomes”

Harris H. Wang, PhD Columbia University-“Spatial metagenomics, culturomics, and engineering of human and environmental microbiomes”

BWH Computational Pathology Special Seminar

Harris H. Wang, PhD
Associate Professor of Systems Biology
Interim Chair, Department of Systems Biology, Columbia University

Microbes that colonize the gastrointestinal tract play important roles in host metabolism, immunity, and homeostasis. Microbes that live in soil are responsible for a variety of key decomposition and remediation activities in the biosphere. Better tools to study and alter these microbiomes are essential for unlocking their vast potential to improve human health and combat climate change. This talk will describe our recent efforts to develop next-generation tools to study and modify microbial communities. Specifically, I will discuss new advances in spatial metagenomics, AI-enabled culturomics, and precision microbiome editing to program different microbiomes with new traits. These capabilities provide a foundation to accelerate the development of microbiome-based products and therapies.

Research Links:

Harris Wang is an Associate Professor of Systems Biology and serves as the Interim Chair of the Department of Systems Biology at Columbia University, Vagelos College of Physicians and Surgeons. He is also jointly appointed the Department of Pathology and Cell Biology. Dr. Wang received his B.S. degrees in Mathematics and Physics from MIT and his Ph.D. in Biophysics from Harvard University. His research group mainly develops enabling genomic technologies to characterize the mammalian gut microbiome and to engineer these microbes with the capacity to monitor and improve human health. Dr. Wang is an Investigator of the Burroughs Wellcome Fund and the recipient of numerous awards, including the Vilcek Prize for Creative Promise in Biomedical Science, Blavatnik National Award Finalist, NSF CAREER, Sloan Research Fellowship, and the Presidential Early Career Award for Scientists and Engineers (PECASE).

Date: Friday October 27, 2023
Time:  2:00-3:00pm ET
In Person: Wolf Conference Center, Hale BTM 02006B, 60 Fenwood Rd Boston 02115
Meeting ID: 891 9982 9402

Gerber Lab awarded $3.1 Million Five Year NIH-NIGMS R35 Grant “Probabilistic deep learning models and integrated biological experiments for analyzing dynamic and heterogeneous microbiomes”

Gerber Lab awarded $3.1 Million Five Year NIH-NIGMS R35 Grant “Probabilistic deep learning models and integrated biological experiments for analyzing dynamic and heterogeneous microbiomes”

This work will leverage deep learning technologies to advance the microbiome field beyond finding associations in data, to accurately predicting the effects of perturbations on microbiota, elucidating mechanisms through which the microbiota affects the host, and improving bacteriotherapies to enable their success in the clinic. New deep learning models will be developed that address specific challenges for the microbiome, including noisy/small datasets, highly heterogenous human microbiomes, the need for direct interpretability of model outputs, complex multi-modal datasets, and constraints imposed by biological principles. Computational models and biological experiments will be directly coupled through reinforcing cycles of predicting, testing predictions with new experiments, and improving models. An important objective will also be to make computational tools widely available to the research community, through release of quality open-source software.



Tal Korem PhD, Columbia – “Contamination and genomic variability in microbiome data”

Microbiome studies hold tremendous potential along with substantial computational challenges. I will present two computational approaches for microbiome data analysis. First, I will present SCRuB, a new method for in silico removal of contamination from microbiome data. We show that modeling the taxonomic composition of contamination sources, rather than trying to infer whether specific taxa are categorically contaminant, allows for more robust decontamination and improves downstream phenotypic prediction. Second, I will present copangraph, a new graph-based approach for representing genomic variability within and across microbiomes. We demonstrate a hybrid co-assembly approach that yields high-quality representation of the microbiome.

Tal Korem’s research program focuses on the development of computational methods that identify and interpret host-microbiome interactions in various clinical setting. The ultimate goal of his research is to translate microbiome findings to clinical care, with microbiome-based therapeutics and microbiome-informed clinical practices. He has developed several approaches for microbiome data analysis, inferring microbial growth rates, structural variants, and microbiome-metabolite interactions; and has applied these methods in diverse clinical and biological investigations, most notably for personalization of dietary treatment and predicting preterm birth. He is a member of Columbia’s Program for Mathematical Genomics (PMG), an Assistant Professor in the Departments of Systems Biology and Obstetrics & Gynecology, and was previously a CIFAR-Azrieli global scholar by the Canadian Institute for Advanced Research.

All Welcome! Note this event will take place on Zoom:

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