The laboratory of Dr. Pradeep Natarajan at the Massachusetts General Hospital/Harvard Cardiovascular Research Center (CVRC) and Center for Genomic Medicine (CGM) and Broad Institute of Harvard & MIT has a unique postdoctoral position open for a highly qualified applicant interested in investigating the genetics and biology of cardiovascular diseases using human genetics across diverse epidemiological cohorts, hospital-based biobanks, and within clinical trials. This position will leverage stimulating environments and resources across world-class institutions. Individuals will work with a range of genetic datasets, including genome-wide arrays, whole exome sequencing, and whole genome sequencing.
Please visit http://natarajanlab.mgh.harvard.edu for additional details about prior, ongoing, and future research. The successful candidate will be jointly closely mentored by Dr. Natarajan. At the completion of training, individuals will be highly trained in a broad spectrum of scalable statistical genetic approaches, integrative genomic analyses, conventional epidemiology, and phenotype classification algorithms applicable to multiple fields of research in human health and biology.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
- Implement quality control, genotype-phenotype association, and fine mapping analyses for genome-wide arrays, whole exome sequencing, and whole genome sequencing studies.
- Integrate data from publicly-available datasets to bioinformatically test biological hypotheses.
- Develop novel integrative genomics analyses from orthogonal dense clinical and biochemical phenotypes.
- Analyses of retrospective and prospective longitudinal data for risk prediction modeling.
- Extraction and modeling of phenotypes using conventional and machine learning algorithms.
- Ability to independently conduct hypothesis-driven research
- Strong record of productivity, motivation, and adaptability
- Ability to work collaboratively, with excellent oral and written communication skills
- Strong background in computational biology, bioinformatics, and biostatistics
- Prior experience in human genetic analyses and bioinformatics analyses of publicly available datasets
- Strong proficiency in UNIX and R; Python proficiency strongly preferred
- Experience with cloud computing is strongly preferred
- Knowledge of cardiovascular disease is not required
- PhD in computational biology, biomedical informatics, biostatistics, statistical genetics, genetic epidemiology, or computer science