Post Doctoral Fellow - Quantitative and Statistical Genetics

Clemson University: College of Science: Genetics & Biochemistry
Post Doctoral Fellow - Quantitative and Statistical Genetics

Location: Greenwood, SC

The laboratory of Dr. Fabio Morgante at the Clemson University Center for Human Genetics (CHG; https://scienceweb.clemson.edu/chg/) invites applications for a postdoctoral fellow, jointly supervised by Dr. Trudy Mackay, as part of the recently awarded NIH COBRE in Human Genetics grant.

The Morgante Lab works on fundamental problems related to quantitative and statistical genetics. In particular, research in his lab focuses not only on understanding the genetic architecture of complex traits and diseases, but also on using this information to improve phenotypic prediction accuracy for such traits. To achieve this goal, his group works at the intersection of genetics, data science, and statistics. More information can be found at https://morgantelab.com/.

The responsibilities of the successful candidate will include (but not be limited to):

• Developing statistical methods for the analysis of complex traits (e.g., to account for context-dependent effects).
• Analyzing large human genetic and phenotypic datasets (e.g., UK Biobank).
• Publishing manuscripts.
• Giving presentations at national and/or international meetings.

The fellow will work closely with Drs. Morgante and Mackay and other members of their groups as well as collaborators. The fellow will also benefit greatly from the close interaction with members of the Duren Lab (https://durenlab.com/) and other labs at the CHG as well as researchers and clinicians at the Greenwood Genetic Center (https://www.ggc.org/).

Informal inquiries about the position are welcome can be sent to fabiom@clemson.edu

QUALIFICATIONS

Applicants must have a Ph.D. in Quantitative Genetics, Statistical Genetics, Computational Biology or other quantitative disciplines.

Applicants should have excellent working knowledge in one or more programming languages, e.g., R, Python or C/C++ and experience working in a High-Performance Computing environment. Applicants with previous experience analyzing large scale genomic and phenotypic data (not necessarily in humans) are especially desirable.

APPLICATION INSTRUCTIONS

Please submit a brief statement of interest, CV, and the names and contact information for at least 3 references to http://apply.interfolio.com/85509.

Applications submitted by May 15, 2022 will receive full consideration.

Review of applications will begin immediately.

The position will be posted until it is filled.

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Clemson University is an AA/EEO employer and does not discriminate against any person or group on the basis of age, color, disability, gender, pregnancy, national origin, race, religion, sexual orientation, veteran status or genetic information. Clemson University is building a culturally diverse faculty and staff committed to working in a multicultural environment and encourages applications from minorities and women.

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