Postdoctoral Fellowship in Computational Immunology

Organization
Johns Hopkins University
Job Location
Baltimore, MD
Salary
NIH level
Job Description

The Larman Laboratory is situated within the Immunology Division of the Pathology Department at the Johns Hopkins School of Medicine, in Baltimore, Maryland, USA. Here we develop and deploy massively parallel DNA sequencing-based molecular assays to better understand human immune responses. The lab is currently seeking applicants for a postdoctoral fellowship. Phage ImmunoPrecipitation sequencing (PhIP-seq) is a powerful proteo-genomic technique that we have pioneered for profiling antibodies against both self and microbial “peptidome” libraries (Larman et al, Nat Biotech, 2011; Xu et al, Science, 2015). PhIP-seq process automation and low per-sample costs enable experimental inquiries on a scale that was previously inaccessible. The successful applicant will develop and utilize cutting edge data mining approaches to extract biological meaning from our immense and growing database of antibody binding specificities and immune repertoires. Our research interests include immuno-oncology, autoimmune disease, viral-related illnesses, and basic immunology.

Requirements

Applicants should be highly motivated, independent, and very hard working. A strong background in data science is required. Applicants must also have a clear record of achievement.

 

How to Apply

To apply, please submit your CV and a cover letter describing why your qualifications are specifically suitable for this position to: hlarman1[AT]jhmi[DOT]edu
You can visit us on the web at http://labs.pathology.jhu.edu/larman/

About Our Organization

Johns Hopkins Medicine is an integrated global health enterprise and one of the leading health care systems in the United States. Diverse and inclusive, Johns Hopkins Medicine educates medical students, scientists, health care professionals and the public; conducts biomedical research; and provides patient-centered medicine to prevent, diagnose and treat human illness.

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