Posdoctoral Fellow Positions in Epidemiology & Multi-Omics Division of Network Medicine BWH and HMS – Boston, Massachusetts

The Channing Division of Network Medicine, Brigham and Women’s Hospital, and Harvard
Medical School are seeking applicants for 3 postdoctoral positions in integrative omic analysis of
asthma, lung function, and aging. All projects provide a terrific opportunity to work with large,
deeply-phenotyped human populations with a focus on the integrative multiomic analysis. The ideal
candidate will have a strong background in programming or statistics together with a familiarity with
bioinformatics tools. No wet lab or laboratory experience is desired or required. All projects are
jointly supervised by Assistant Professor Michael McGeachie and Associate Professor Jessica Lasky-
Su, or by Dr Lasky-Su alone, but it will also include interacting with a highly-interdisciplinary team
of researchers from both the Channing and elsewhere in the Longwood Medical Area, Boston MA.

Project 1: The position will focus on the analysis of microRNA-Seq and metabolomics profiling data
from a Biobank cohort with asthma, with additional integrative omic investigations including the
integration of genomic variants and DNA methylation. We are specifically interested in studying
miRNA and metabolomic influences on asthma progression through lung function, while including
other omic datatypes including genetics, genomics and the microbiome. (Supervisors Drs McGeachie
and Lasky-Su).

Project 2: The position will focus on the analysis of large-scale antibody profiling and metabolomics
profiling data from a Biobank cohort with asthma, with additional integrative omic investigations
including the integration of genomic variants and DNA methylation. Primary goals include studying
infection and metabolomic influences on asthma progression through lung function and other disease
outcomes, while including other omic datatypes including genetics, genomics and the microbiome.
(Supervisor Dr Lasky-Su).

Project 3: The position will focus on the analysis of multi-omic data and electronic medical records
(EMR) from several Biobank cohorts, with additional integrative omic investigations including the
integration of genomic variants and DNA methylation. The main work will be studying aging and
chronic disease trajectories, while integrating omic datatypes including metabolomics, proteomics,
genetics, genomics and the microbiome. (Supervisor Dr Lasky-Su).

The Channing Division of Network Medicine represents a diverse and highly collaborative research
community that is focused on deciphering the etiology of complex diseases. The lab benefits from
active collaborations with computational, biostatistical, and networking experts. We also work with
state-of-the-art laboratories for the generation of ‘omics’ data and have established bioinformatic
pipelines for cleaning and preparing data for analysis. The fellow will primarily be working on the
statistical analysis and scientific write up of projects based within one of our many well-established
longitudinal cohorts of children and adults, which have a wealth of multi-omic data and cover
lifestyle, behavior, dietary and environmental risk factors. These outstanding resources offer the
potential for a high-quality candidate to address scientific questions of interest and to develop their

research career in a vibrant environment. We are seeking highly motivated and analytically-capable
applicants who have a strong interest in progressing the field through impactful science.

QUALIFICATIONS: Applicants should have a Ph.D., Sc.D. or M.D. with a strong analytic
background in genomics, bioinformatics, statistics, epidemiology, computer science, network biology
or related field. Programming proficiency in some language is required (e.g. Java, C, C++, Python,
Perl, SAS, MATLAB or R). Previous experience with analyzing metabolomic and/or next generation
sequencing data is desired. Scientific publications in a peer-reviewed journal are necessary. Excellent
written and verbal communication skills are essential.

To apply, please supply a cover letter describing current research interests and specifically
addressing your interest in the work of the Channing and how your background may uniquely
prepare you for one of the three projects. Applications should also include a CV including contact
information for three references and mail to remmg@channing.harvard.edu and rejpo@channing.harvard.edu.

Brigham and Women’s Hospital is a Harvard Medical School affiliated institution, with over 1000
principal investigators. The Channing Division of Network Medicine is a research division within the
Department of Medicine whose goal is to define the etiology and reclassify complex disease using
network- and systems-based approaches. This group includes some of the largest population-based
and pulmonary cohorts in the world, and an outstanding track record of mentoring.

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 condition or any
other characteristic protected by law. Women and minority candidates are particularly encouraged to
apply.

Appointment and/or employment at a Mass General Brigham affiliate is contingent upon compliance
with all requirements for employment at the MGB affiliate. These requirements include without
limitation:
• United States Citizenship and Immigration Services rules concerning identity and right to
work in the United States
• Multi-state criminal background checks
• Review of the Medicare Sanctions and Exclusions List
• Pre-employment health and drug screening and annual compliance with the Influenza
Vaccination Policy
Any offer of employment is contingent upon satisfactory completion of the above requirements for
employment, as well as satisfactory completion of the credentialing and medical staff appointment
process at the MGB affiliate(s) where the applicant will provide clinical services.
Reference information, including academic and/or employment records, final evaluations, and recommendations for future employment will be required.