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<div><span>The Oden Institute for Computational Engineering and
Sciences and the </span><span style="font-size: 11pt">Department
of Statistics and Data Science at The University of Texas </span><span>at
Austin have an opening for a tenured or tenure-track faculty </span><span style="font-size: 11pt">position beginning Fall 2026 in the area
of Scientific Machine </span><span>Learning and AI for Science.
We are seeking candidates who address </span><span style="font-size: 11pt">challenging scientific and technological
problems through advances in </span><span style="font-size: 11pt">statistical and mathematical AI and ML
theory and algorithms. Examples </span><span style="font-size: 11pt">of topics of interest include:
statistically-principled methods for </span><span style="font-size: 11pt">uncertainty quantification; operator
learning and learned surrogates </span><span style="font-size: 11pt">with clear statistical validation;
Bayesian inverse problems and data </span><span style="font-size: 11pt">assimilation via measure transport and
amortized inference; robustness </span><span style="font-size: 11pt">and distribution shift in scientific ML;
causal inference for </span><span style="font-size: 11pt">mechanistic
systems; and sequential experimental design and control </span><span style="font-size: 11pt">(including reinforcement learning) under
uncertainty. These topics are </span><span style="font-size: 11pt">meant as illustrations, and not as an
exhaustive list. This search is </span><span style="font-size: 11pt">being conducted jointly by the Oden
Institute and the Department of </span><span style="font-size: 11pt">Statistics and Data Science as part of a
campus-wide commitment to </span><span style="font-size: 11pt">expanding
the development of AI for Science and Scientific Machine </span><span style="font-size: 11pt">Learning at UT Austin. The successful
candidate will have half of </span><span style="font-size: 11pt">their teaching duties in the Oden
Institute's Computational Science, </span><span style="font-size: 11pt">Engineering and Mathematics (CSEM)
graduate program and half in the </span><span style="font-size: 11pt">Department of Statistics and Data
Science. This position is open to </span><span style="font-size: 11pt">applicants at all ranks, with a
preference for hiring at the assistant </span><span style="font-size: 11pt">or associate professor level. </span></div>
<div><span> </span></div>
<div><span>To submit an application, see </span><span style="font-size: 11pt"><a href="https://apply.interfolio.com/174449." title="Unmangled Microsoft Safelink">apply.interfolio.com/174449.</a>
Review of applications will begin </span><span style="font-size: 11pt">November 15, 2025, and will continue
until an appropriate candidate is </span><span style="font-size: 11pt">identified. We anticipate virtual
interviews in December and in-person </span><span style="font-size: 11pt">campus interviews in early 2026. Please
address questions to </span><span style="font-size: 11pt">Prof.
Omar Ghattas and Prof. Alessandro Rinaldo, SciML/AI Faculty </span><span style="font-size: 11pt">Search Committee Co-Chairs
(<a class="moz-txt-link-abbreviated" href="mailto:omar@oden.utexas.edu">omar@oden.utexas.edu</a>, </span><span style="font-size: 11pt"><a class="moz-txt-link-abbreviated" href="mailto:alessandro.rinaldo@austin.utexas.edu">alessandro.rinaldo@austin.utexas.edu</a>).
For application questions, </span><span style="font-size: 11pt">contact
Ruth Park (<a class="moz-txt-link-abbreviated" href="mailto:ruth.park@oden.utexas.edu">ruth.park@oden.utexas.edu</a>). </span></div>
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Omar Ghattas<br>
Oden Institute for Computational Engineering & Sciences<br>
The University of Texas at Austin<br>
<a class="moz-txt-link-abbreviated" href="mailto:omar@oden.utexas.edu">omar@oden.utexas.edu</a><br>
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