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<b>The Department of <i><u>Hydrology and Atmospheric Sciences</u></i> at the <i>University of Arizona </i></b>invites applications for a <i><u>tenure-eligible</u></i> <b><i>Assistant Professor in Quantitative Spatio-Temporal Data-Science</i></b> (statistical
and machine-learning methods) as applied to <b><i>The Hydrologic and Atmospheric Sciences</i></b> to begin August 2023. The successful candidate will advance the University of Arizona’s research and teaching in the use of such methods to understand and predict
the dynamical evolution and interaction of hydro-meteorological (and related) process on the land and in the atmosphere, and their applications to engineering solutions and decision making. The distribution of effort will normally be 40% Research, 40% Teaching,
and 20% Service.</p>
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See attached for the full job announcement.</p>
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Please apply and learn about the position at the link below:</p>
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<i><span style="font-size:12pt"><font color="#954f72"><a href="https://arizona.csod.com/ux/ats/careersite/4/home?c=arizona&sq=req12308">https://arizona.csod.com/ux/ats/careersite/4/home?c=arizona&sq=req12308</a></font></span></i></p>
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Avelino F. Arellano, Jr., Ph.D. (he/him/his)<br>
Associate Professor<br>
Department of Hydrology and Atmospheric Sciences</div>
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GIDP Remote Sensing and Spatial Analysis</div>
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GIDP Applied Mathematics<br>
University of Arizona<br>
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(tel) 1-520-626-3015<br>
(email) afarellano@email.arizona.edu<br>
(web) arellano.faculty.arizona.edu</div>
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(add) 314C JW Harshbarger Bldg, Tucson, AZ 85721</div>
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(zoom) https://arizona.zoom.us/my/ave.arellano<br>
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