Emory

Post Doctoral Fellow - Human Genetics- Yang Lab

Job Number
59581
Job Type
Regular Full-Time
Division
School Of Medicine
Department
SOM: Hum Gen: Admin
Location : Name
Emory Campus-Clifton Corridor
This position may involve the following Health and Safety issues:
Not Applicable
Required Documents
Cover letter, Personal Statement, Reference Letters, Research Interests, Sample Published Paper

Discover Your Career at Emory University

Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can contribute to the diversity and excellence of our academic community.

Description

The candidate will be expected to work on statistical/computational method & tool development for studying genomics data of complex diseases, statistical data analysis, and publishing on decent journals. The candidate will have opportunities to collaborate with members of the Center for Computational and Quantitative Genetics (http://ccqg.emory.edu/about/index.html), as well as people from diverse departments (e.g., Human Genetics, Neurology, Biostatistics and Bioinformatics, Psychology) at Emory University.
                            
The candidate is expected to have a Ph.D. degree in Statistics/Biostatistics, Bioinformatics, Computer Science or other relevant disciplines, with interests in Statistical Genetics and strong quantitative research background; proficiency in one or multiple of the popular programming languages, e.g., R, Python, C++, Perl; experience working with large genomics data, next-generation sequence data, and high-performance clusters with Linux environment are desirable.
                           
The Yang Lab (https://yanglab-emory.github.io/) is located in the Center for Computational and Quantitative Genetics, Department of Human Genetics (http://genetics.emory.edu/index.html), Emory University School of Medicine. We mainly focus on development and application of statistical methods (e.g., Bayesian methods, Machine Learning and Deep Learning methods) for integrative analysis with multi-omics data (genetic, epigenetic, transcriptomic, and proteomic data), with the goal of understanding the underlying genomic architecture of complex traits and diseases.

Additional Requirements: Cover Letter, CV, Brief Statement of Research & Interest (less than 2 pages), one Sample Publication and Contacts for 3 references.

 

 

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Emory University is dedicated to providing equal opportunities and equal access to all individuals regardless of race, color, religion, ethnic or national origin, gender, genetic information, age, disability, sexual orientation, gender identity, gender expression, and veteran's status. Emory University does not discriminate in admissions, educational programs, or employment on the basis of any factor stated above or prohibited under applicable law. Students, faculty, and staff are assured of participation in University programs and in the use of facilities without such discrimination. Emory University complies with Executive Order 11246, as amended, Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veteran's Readjustment Assistance Act, and applicable executive orders, federal and state regulations regarding nondiscrimination, equal opportunity and affirmative action. Emory University is committed to achieving a diverse workforce through application of its affirmative action, equal opportunity and nondiscrimination policy in all aspects of employment including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training. Inquiries regarding this policy should be directed to the Emory University Department of Equity and Inclusion, 201 Dowman Drive, Administration Building, Atlanta, GA 30322.

 

Emory University is committed to providing reasonable accommodations to qualified individuals with disabilities upon request. To request this document in an alternate format or to request a reasonable accommodation, please contact the Department of Accessibility Services at 404-727-9877 (V) | 404-712-2049 (TDD). Please note that one week advance notice is preferred.

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