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<p>The Department of Mathematics at the University of Arizona<br>
is seeking Postdoctoral Research Associates with research<br>
interests in the intersection of modern applied &<br>
computational mathematics, statistics & data science, and<br>
applications to physical, biological, and engineered<br>
systems. Subject to the availability of funding, these<br>
postdoctoral positions (non-tenure eligible) with an<br>
appointment beginning in Fall 2023. Review will begin<br>
December 1 and will continue until filled. US citizenship<br>
or permanent residency required.<br>
<br>
The positions are specific to the Research Training Group<br>
(RTG) in Applied Mathematics and Statistics for Data-Driven<br>
Discovery at the University of Arizona. The RTG conducts<br>
vertically integrated training in diverse research areas,<br>
including (but not limited to) physics-informed machine<br>
learning for data-driven modeling and model reduction in<br>
multi-physics dynamical systems, biological fluid dynamics,<br>
bioinformatics of gene regulatory networks, medical imaging,<br>
high dimensional and complex data analysis and statistical<br>
inference, natural language processing, topological data<br>
analysis and continuum mechanics, data assimilation and<br>
uncertainty quantification, and physiological time series<br>
analysis, with an emphasis on the design, analysis, and<br>
application of modern machine learning and computational<br>
statistics techniques.<br>
<br>
Successful candidates will conduct teaching and research in<br>
the Department of Mathematics, with close mentoring by an<br>
RTG faculty member. Current RTG faculty are Mathematics /<br>
Applied Math / Statistics faculty Misha Chertkov (co-PI),<br>
David Glickenstein (co-PI), Ning Hao, Leonid Kunyansky,<br>
Kevin Lin (PI), Laura Miller (co-PI), Yue (Selena) Niu,<br>
Marek Rychlik, Shankar Venkataramani, and Hao Helen Zhang<br>
(co-PI), as well as Ali Bilgin (Biomedical & Electrical<br>
Engineering) and Megha Padi (Molecular Biology).<br>
<br>
For more information and to apply for the position, see<br>
<a href="https://www.mathjobs.org/jobs/list/21300" title="Unmangled Microsoft Safelink">www.mathjobs.org/jobs/list/21300</a>
. Please direct<br>
all questions to Kevin Lin .<br>
<br>
-- <br>
=======================<br>
Kevin K Lin, PhD<br>
PI, Research Training Group in Data Driven Discovery<br>
Mathematics / University of Arizona<br>
<a href="https://www.math.arizona.edu/~klin" title="Unmangled
Microsoft Safelink">www.math.arizona.edu/~klin</a></p>
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