Research Fellow - Computational Cardiology Research, Honigberg Lab, MGH Cardiovascular Research Center

Mass General Brigham•Boston, MA

6d•Onsite

About The Position

The laboratory of Dr. Michael Honigberg at the Massachusetts General Hospital Cardiovascular Research Center (CVRC) and Broad Institute of MIT & Harvard has a unique post-doctoral fellow position open for a highly qualified applicant interested in investigation at the intersection of cardiovascular, reproductive, and aging biology. The new hire will be appointed as a Research Fellow at the Massachusetts General Hospital and Post-Doctoral Fellow at Harvard Medical School. The Honigberg lab aims to advance mechanistic understanding of emerging cardiovascular risk factors and inform new paradigms for health promotion and disease prevention. Current projects focus on pregnancy (e.g., preeclampsia/eclampsia), menopause, aging biology, and novel lipid-modifying therapies, among other topics. This position will enable access to resources and opportunities across multiple world-class institutions. Individuals will work with a range of data types, including genetic datasets, including genotype arrays, whole exome and whole genome sequencing, single-cell sequencing, and multi-omic data (e.g., metabolic, transcriptomic, proteomic, methylation). The successful candidate will work within a dynamic and highly collaborative environment alongside computational biologists, bioinformaticians, epidemiologists, clinicians, research coordinators, students, and medical trainees.

Requirements

Doctoral degree in computational biology, biomedical informatics, biostatistics, statistical genetics, genetic epidemiology, or computer science.
First (or co-first) author of one or more peer-reviewed scientific publications.
Excellent English verbal and written communication skills.
Able to work both independently and in a team.
Strong record of productivity, motivation, adaptability, and collaboration.
Exceptional oral and written communication skills.
Strong background in computational biology and bioinformatics.
Strong demonstrable proficiency in UNIX, R, Python, and Perl; facility with Java, Matlab, C, C++ preferred.
Strong facility with cloud computing.
Prior experience in human genetic analyses and bioinformatics analyses of publicly available datasets.
Ability to adapt to rapidly changing and high-demand environments.

Nice To Haves

Strong skills in statistical analyses are highly preferred.
Familiarity with next-generation sequence data analysis tools strongly preferred.
Knowledge of cardiovascular disease is not required.

Responsibilities

Construction and implementation of cloud-based pipelines for genomic, polygenic risk scoring, and biostatistical analyses.
Processing and quality control of next-generation sequencing data.
Processing and quality control of multi-omics data.
Statistical analyses of genotype-phenotype association analyses, with summarization and graphical representations.
Organizing, manipulating, and harmonizing new datasets across different formats and synchronization with existing datasets and databases.
Phenotypic curation from electronic health record structured and unstructured data.
Construction, implementation, and sensitivity analyses of biostatistical models in classical epidemiology, genetic epidemiology, and machine learning.
Lead and contribute to manuscript preparation as well as internal and external project-team reports.
Actively participate and present in project meetings and lab meetings.