- Developing novel statistical methods and tools to identify novel genetic risk factors for human disease onset and progression.
- Leveraging large-scale biobanks with longitudinal electronic health records (EHRs) to understand genetics of human disease progression.
- Applying cutting-edge statistical tools to map and harmonize genetics of rare and common variations for molecular phenotypes measured at single-cell and bulk resolution.
- Developing novel statistical tools to improve the power to identify disease gene association by integrating epigenetics and xQTLs to GWAS.
- First author of one or more peer-reviewed scientific publications or a preprint archive
- Excellent English verbal and written communication skills
- Fast learner, analytical thinker, creative, "hands-on", team-player.
- Demonstrated proficiency in Unix, Python, R, or C .
- Experience in working in HPC and/or cloud-based environment.
- Motivation to translate the developed research into publications.
- Able to work both independently and collaborate with other scientists, postdoctoral fellows, and PIs in a collegial work environment with intellectual rigor.
- Experience with analyzing high-dimensional datasets is preferred.
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Some fluency with biology and/or genetics is ideal, as is the ability to adapt quickly to a cross-functional team in a rapidly changing environment.
- First author of one or more peer-reviewed scientific publications or a preprint archive
- Excellent English verbal and written communication skills
- Fast learner, analytical thinker, creative, "hands-on", team-player.
- Demonstrated proficiency in Unix, Python, R, or C .
- Experience in working in HPC and/or cloud-based environment.
- Motivation to translate the developed research into publications.
- Able to work both independently and collaborate with other scientists, postdoctoral fellows, and PIs in a collegial work environment with intellectual rigor.
- Experience with analyzing high-dimensional datasets is preferred.
-
Some fluency with biology and/or genetics is ideal, as is the ability to adapt quickly to a cross-functional team in a rapidly changing environment.
-
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Post-Doctorate Research Fellow - Boston, United States - Massachusetts General Hospital
Description
GENERAL SUMMARY/ OVERVIEW STATEMENT:
The Zhou Lab ) and the Neale Lab ) in the Center for Genomic Medicine at the Massachusetts General Hospital, Harvard Medical School, are jointly seeking highly motivated postdoctoral fellow candidates.
The new hire will be appointed as a Research Fellow at the Massachusetts General Hospital and Postdoc at the Harvard Medical School and will be affiliated with the Broad Institute of MIT and Harvard.
Successful candidates are expected to excel at critical thinking, be quick learners for new analytical approaches, and capable of applying or developing novel computational methods for solving complex problems.
A strong background in statistics, biostatistics, computer science and/or computational biology is required; and specifically, experience with analyzing high-dimensional datasets, such as whole-genome sequencing, multi-omics data, and electronic health records, is preferred.
Some fluency with biology and/or genetics is ideal, as is the ability to adapt quickly to a cross-functional team in a rapidly changing environment.
Postdocs will have the opportunity to help shape the lab culture, where ideas are freely shared, and contributions are highly valued.
We are dedicated to developing and applying novel efficient computational methods for the identification and interpretation of genomic variations for human disease, particularly for psychiatric disorders.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
The Postdoctoral Fellow will work on understanding genetics of human diseases and traits by leveraging large-scale biobanks and multi-omics data sets.
Possible areas of research include:
SKILLS & COMPETENCIES REQUIRED:
The ideal candidate should have received (or expect to receive soon) a Ph.
D. in statistics, biostatistics, genetics, computational biology, bioinformatics, computer science and/or related field.
Not required, but preferred qualifications:
SKILLS & COMPETENCIES REQUIRED:
The ideal candidate should have received (or expect to receive soon) a Ph.
D. in statistics, biostatistics, genetics, computational biology, bioinformatics, computer science and/or related field.
Not required, but preferred qualifications:
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