Job ID:
Job date: 2018-03-09
End Date:
Company : Dana-Farber Cancer Institute Country : Role : Postdoc
Job date: 2018-03-09
End Date:
Company : Dana-Farber Cancer Institute Country : Role : Postdoc
Job Description:
A post-doctoral position is available in the statistical genetics research group of Dr. Alexander (Sasha) Gusev, a faculty member at the Dana-Farber Cancer Institute and the Brigham & Women's Division of Genetics. The fellow will work closely with Dr. Gusev, and with collaborators at Dana-Farber Cancer Institute, HSPH/HMS, The Broad Institute, and the BWH Center for Data Sciences. Successful applicants will have the opportunity to design their own projects relating these and other concepts. Qualifications: Candidates should have a Ph.D. in genetics, functional genomics, computer science, statistics, bioinformatics, computational biology, or a related quantitative research field; strong quantitative skills including proficiency in at least one programming language; a publication record. Knowledge of complex trait mapping, medical genetics and/or population genetics is a plus. Statistically or computationally minded applicants without direct experience in cancer genetics are welcome.
Additional Info:
The lab (http://www.gusevlab.org) focuses on developing computational methods to understand the heritable component of cancer and common diseases by leveraging large-scale data. Our research interests include (but are not limited to): (1) Integrating molecular phenotypes such as gene expression and chromatin activity to decipher disease mechanisms and perform statistical causal inference. (2) Understanding and quantifying the relationship between heritable/germline and somatic variation in cancer and it's impact on personalized clinical decision-making. (3) Inferring complex trait architecture at genome scale. (4) Quantifying genetic genealogy in massive cohorts and relating it to clinical phenotypes. Though the lab's focus is on statistical/quantitative methods, we collaborate broadly with experimentalist groups to validate and inform our statistical hypotheses. Please be prepared to provide a brief statement of interest, CV, and contact information for three references. [Click Here to Access the Original Job Post]
A post-doctoral position is available in the statistical genetics research group of Dr. Alexander (Sasha) Gusev, a faculty member at the Dana-Farber Cancer Institute and the Brigham & Women's Division of Genetics. The fellow will work closely with Dr. Gusev, and with collaborators at Dana-Farber Cancer Institute, HSPH/HMS, The Broad Institute, and the BWH Center for Data Sciences. Successful applicants will have the opportunity to design their own projects relating these and other concepts. Qualifications: Candidates should have a Ph.D. in genetics, functional genomics, computer science, statistics, bioinformatics, computational biology, or a related quantitative research field; strong quantitative skills including proficiency in at least one programming language; a publication record. Knowledge of complex trait mapping, medical genetics and/or population genetics is a plus. Statistically or computationally minded applicants without direct experience in cancer genetics are welcome.
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Additional Info:
The lab (http://www.gusevlab.org) focuses on developing computational methods to understand the heritable component of cancer and common diseases by leveraging large-scale data. Our research interests include (but are not limited to): (1) Integrating molecular phenotypes such as gene expression and chromatin activity to decipher disease mechanisms and perform statistical causal inference. (2) Understanding and quantifying the relationship between heritable/germline and somatic variation in cancer and it's impact on personalized clinical decision-making. (3) Inferring complex trait architecture at genome scale. (4) Quantifying genetic genealogy in massive cohorts and relating it to clinical phenotypes. Though the lab's focus is on statistical/quantitative methods, we collaborate broadly with experimentalist groups to validate and inform our statistical hypotheses. Please be prepared to provide a brief statement of interest, CV, and contact information for three references. [Click Here to Access the Original Job Post]