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The Network Systems Science & Advanced Computing (NSSAC) Division of the
Biocomplexity Institute & Initiative at the University of Virginia is
seeking postdoctoral associates for multiple positions in machine learning,
data analytics, and high-performance computing. The Biocomplexity Institute
performs world-class informatics research in life sciences, social
sciences, and human health by integrating theory, modeling and simulation
with computational and experimental science in a transdisciplinary, team
science research environment. The NSSAC Division uses information science
to create solutions for complex societal problems. Our simulation systems
are critical to the success of detecting new threats, natural and man-made,
and planning strategic responses. Application areas include computational
epidemiology, computational biology, computational social science, and more.

This position provides the opportunity to work with a large team of
researchers working on a diverse range of projects ranging from genomic
analysis to large-scale simulations of social systems. The postdoctoral
researcher will work on developing novel machine learning, data analytics,
and HPC methods and will contribute to multiple projects funded through
DARPA, NSF, NIH, NASA, IARPA, and others.

Required Qualifications:

   - Applicants must have received or be on track to receive a PhD in
   Artificial Intelligence, Machine learning, high-performance computing, or
   in a very closely related field by May of 2019 and must hold a PhD at the
   time of appointment. Preferred application areas include urban science and
   analytics, biosystems and social sciences.
   - Experience programming in java, python, or C++
   - Excellent communication skills, both oral and written, demonstrated
   through the development of publications and delivery of presentations.

Desired Qualifications:

   - Research experience with big data, multi-scale simulation systems and
   machine learning
   - Experience with databases and computing on clusters.
   - Programming for parallel computing

In addition, the candidate must be motivated, enthusiastic, self-driven and
have demonstrated the ability to work in a highly collaborative team
science environment.


Upload the following materials at
(Requisition number R0003518):

   - Cover Letter detailing your relevant experience and interest in the
   position and summary of your coursework
   - CV
   - Contact information for three references

In addition, please have three confidential letters of reference sent to
this email address: [log in to unmask]

Review of applications will begin on March 7, 2019 and will continue until
the position is filled.

*This is a restricted position based upon the continued availability of
funding. *

The position will be based in Charlottesville, VA, USA. Charlottesville is
home to Thomas Jefferson’s Monticello and the University of Virginia, and
is nestled in a valley surrounded by the picturesque Blue Ridge Mountains
ideal for hiking, mountain biking, and fishing. It has the best of both
worlds: a college town vibe and energy juxtaposed to a chic, cosmopolitan
atmosphere given the numerous restaurants, rooftop bars, breweries and
wineries, boutique stores, theaters, and entertainment venues you’ll find
on the pedestrian Downtown Mall and surrounding area. Charlottesville also
has its fair share of cultural events and festivals, but if you ever need a
big city boost, hop on Amtrak to Washington, D.C. or New York for a weekend
getaway. Guaranteed, you always will be glad to come back.

To learn more about the Biocomplexity Institute and the Network Systems
Science & Advanced Computing Division, please visit us at

For questions about the application process, please contact  Savanna
Galambos, Faculty Search Advisor, at [log in to unmask]

*The University of Virginia, including the UVA Health System and the
University Physician’s Group are fundamentally committed to the diversity
of our faculty and staff.  We believe diversity is excellence expressing
itself through every person's perspectives and lived experiences.  We are
equal opportunity and affirmative action employers. All qualified
applicants will receive consideration for employment without regard to age,
color, disability, gender identity, marital status, national or ethnic
origin, political affiliation, race, religion, sex (including pregnancy),
sexual orientation, veteran status, and family medical or genetic

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