Posting Summary: The laboratories of Dr. Mete Civelek (www.civeleklab.org) and Dr. Mike Guertin (http://guertinlab.org/) at the University of Virginia are looking for a Research Scientist for an NIH-funded computational project. The successful candidate will use publically available datasets to predict functional mechanisms of genomic loci associated with coronary artery disease (1,2). The work is done using molecular data obtained from human populations, primary tissues and human cell lines and programming in UNIX, Python, or R.
What we offer:
1. Training in human and mouse genetics, systems, and computational biology through interactions with lab members and workshops/courses offered on campus. 2. A stimulating environment with freedom to develop new research directions. 3. Regular opportunities to interact with other scientists at the University of Virginia during the scientific meetings organized by the Cardiovascular Research Center, Center for Public Health Genomics, Data Science Institute, and Department of Biochemistry and Genetics. 4. Supportive mentorship for multi-faceted career development and opportunities tailored towards individual career goals. 5. An NIH R21 (HL135230) funded position (with potential for renewal). 6. A research team consisting of diverse group of trainees at the postdoctoral, doctoral, and undergraduate level. 7. University-wide resources for individuals with families and individuals underrepresented in science and engineering (https://graddiversity.virginia.edu/). 8. A department located in Charlottesville, situated at the foothills of Blue Ridge Mountains, with easy access to Shenandoah National Park, Richmond, and Washington D.C. with excellent cost of living. 9. Local start-ups, meetup groups, and community-driven conferences utilizing various aspects of data science.
What we're looking for:
1. Enthusiastic and ambitious individual with a strong interest in our joint research and laboratory environment. 2. Desired background in programming and experience with genomic and genetic datasets. 3. Willingness to learn new computational approaches, designing analysis pipelines independently, and documenting them for public release. 4. Eagerness to apply for grants or fellowships (depending on the career stage) and to take advantage of other career development opportunities. 5. Interest in working with junior lab members and undergraduates. 6. Strong verbal and written communication skills.
Minimum requirements include a Master's degree and demonstrable experience in programming using bioinformatics tools/approaches. Knowledge in human genetics is preferred.
To apply please visit https://jobs.virginia.edu and search on posting number 0623921. Complete a candidate profile and attach a CV, Cover letter and references.
For more information please contact Dr. Mete Civelek at firstname.lastname@example.org.
The University of Virginia is an equal opportunity affirmative action employer. Women, minorities, veterans, and persons with disabilities are encouraged to apply.
Internal Number: 353_85347
About University of Virginia
Founded by Thomas Jefferson, the University of Virginia opened in 1825 as the nation's first public university. A longstanding dedication to preeminence in both scholarship and teaching; top ranking in global satisfaction, collegiality and work/family issues on the COACHE survey of early career faculty; a commitment to excellence that is integrally connected with diversity and a broad array of benefits make the University of Virginia a prime choice for both faculty and staff. The University of Virginia is located in the small cosmopolitan city of Charlottesville near the Blue Ridge Mountains, 70 miles from Richmond and 110 miles from Washington, D.C. The University of Virginia remains the No. 2 best public university in the 2013 edition of the U.S. News and World Report rankings. In the 14 years since U.S. News began ranking public universities as a separate category, U.Va. has ranked either No. 1 or No. 2. U.Va. continues to rank in the Top 25 among the best of all national universities, public and private.