Posted in Other 8 days ago.
GENERAL SUMMARY/ OVERVIEW STATEMENT:
The Ge Laboratory in the Center for Genomic Medicine at the Massachusetts General Hospital, Harvard Medical School, is seeking highly motivated post-doctoral fellow candidates. Our research group develops novel statistical and computational methods to explore the genetic basis of a spectrum of human complex traits and common diseases and to advance precision medicine. Our current research program has particular focuses on: (i) leveraging global biobanks to dissect the genetic architectures of human traits and diseases in diverse populations; (ii) developing scalable and accurate statistical genetic methods such as polygenic prediction and fine-mapping for improved discovery and mapping of common and rare disease-causing variants, and individualized prediction of disease risk and trajectories in clinical settings; (iii) integrating large-scale genomic, neuroimaging, behavioral and clinical data to uncover the genetic and neural underpinnings of brain disorders.
The new hire will be appointed as a Research Fellow at the Massachusetts General Hospital and Post-Doc at the Harvard Medical School.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
The Post-Doctoral Fellow will lead the development of novel statistical and computational methods, and/or perform large-scale genomic, neuroimaging and clinical data analysis to advance the goals of our research program. The Post-Doctoral fellow will be situated in the MGH Center for Genomic Medicine under the guidance and mentorship of Dr. Tian Ge. The fellow will be provided with a vibrant multidisciplinary research environment in close collaboration with the MGH Center for Precision Psychiatry, the Broad Institute, Harvard-affiliated hospitals and several national and international research consortia, as well as training and career development opportunities spanning statistical genetics, psychiatric genetics, neuroimaging genetics, precision medicine and population health.
Qualifications
SKILLS & COMPETENCIES REQUIRED
The ideal candidate should have received (or expect to receive soon) a Ph.D. in human/statistical genetics, applied mathematics, statistics/biostatistics, bioinformatics, computer science, or related field.
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