Postdoctoral Research Position in Statistical Genetics and Genomics | Cambridge, Massachusetts, United States | Harvard University

Position:	Postdoctoral Research Position in Statistical Genetics and Genomics
Institution:	Harvard University
Location:	Cambridge, Massachusetts, United States
Duties:	Postdoctoral Research Fellow position in statistical genetics and genomics is available at Harvard T. H. Chan School of Public Health. This position involves developing and applying statistical and machine learning methods for analysis of high-throughput genetic and genomic data, including large scale Whole Genome Sequencing association studies, integrative analysis of genetic and genomic data, high-dimensional phenotype analysis, causal mediation analysis and Mendelian Randomization, Polygenic risk scores, and analysis of biobanks. We seek an individual with strong statistical, computing, and genetic backgrounds and who has expertise in statistical and computational methods for big data, statistical genetics and genomics. The work will involve both methodological research with department faculty and collaboration with subject matter researchers and investigators in large consortia
Requirements:	Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, strong quantitative research background, statistical and programming proficiency, strong genetic knowledge, as well as good written and oral communication skills

Text:	Skip to Main Content Explore Academic Positions at Harvard Toggle navigation Home Search Jobs Log In /Create Account Help Postdoctoral Research Position in Statistical Genetics and Genomics Bookmark this Posting \| Print Preview \| Apply for this Job Position Details Title Postdoctoral Research Position in Statistical Genetics and Genomics School Harvard T.H. Chan School of Public Health Department/Area Biostatistics Position Description Postdoctoral Research Fellow position in statistical genetics and genomics is available at Harvard T. H. Chan School of Public Health. This position involves developing and applying statistical and machine learning methods for analysis of high-throughput genetic and genomic data, including large scale Whole Genome Sequencing association studies, integrative analysis of genetic and genomic data, high-dimensional phenotype analysis, causal mediation analysis and Mendelian Randomization, Polygenic risk scores, and analysis of biobanks. We seek an individual with strong statistical, computing, and genetic backgrounds and who has expertise in statistical and computational methods for big data, statistical genetics and genomics. The work will involve both methodological research with department faculty and collaboration with subject matter researchers and investigators in large consortia. Basic Qualifications Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, strong quantitative research background, statistical and programming proficiency, strong genetic knowledge, as well as good written and oral communication skills. Additional Qualifications Special Instructions Administrative questions regarding this position can be sent to Susan Luvisi at biostat_postdoc@hsph.harvard.edu. Scientific questions regarding this position can be sent to Xihong Lin at xlin@hsph.harvard.edu. Contact Information Susan Luvisi Contact Email biostat_postdoc@hsph.harvard.edu Equal Opportunity Employer 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 conditions or any other characteristic protected by law. Minimum Number of References Required 3 Maximum Number of References Allowed 5 Keywords Supplemental Questions Required fields are indicated with an asterisk (*). Applicant Documents Required Documents Curriculum Vitae Cover Letter Optional Documents Trademark Notice \| Harvard University Copyright © 2015 The President & Fellows of Harvard College ")); To ensure the security of your data, you will be logged out due to inactivity in 3 minutes at . Any data not saved will be lost. Click 'OK' to keep your session active.