Connectionists: [Assistant Professor] MATRIX AI Consortium (University of Texas at San Antonio) in AI Accelerators Area

[Dhireesha Kudithipudi]

Over the past two years, The University of Texas at San Antonio (UTSA) has
made significant progress in interdisciplinary AI research and scholarship
efforts, notably through the newly launched MATRIX <https://ai.utsa.edu/>
AI Consortium and establishing the School of Data Science. UTSA has a
focused hiring plan in the area of Artificial Intelligence, specifically in
Inclusive & Human-Centered AI Systems and AI Accelerators, both of which
advance the research thrusts in the MATRIX <https://ai.utsa.edu/> . The
initiative will serve as the nexus for leading AI innovators to perform
transdisciplinary research, engage in high-impact partnerships, and provide
thought leadership and domain expertise to solve intractable problems in
AI.


*Highlighted position: *Assistant Professor in the field of AI Accelerators
will have an appointment in the Department of Electrical and Computer
Engineering.

The required qualifications of the successful candidates are a doctorate
degree in Computer Engineering, Computer Science, Electrical Engineering,
and/or related fields, with appropriate research and teaching record for
appointment at the rank for each position (for those seeking appointments
with tenure, this is contingent upon Board of Regents’ approval), and
demonstrated commitment to inclusion and diversity. Successful candidates
will demonstrate (1) a record of high-quality research and scholarship, or
for assistant professor candidates, demonstration of a solid research
agenda and publication and external funding capability, (2) excellence in
undergraduate and graduate education or demonstration of ability to teach,
and (3) a demonstrated commitment to inclusion and diversity.

*AI Accelerators: *Outstanding candidates at the Assistant Professor level
are invited for a position in “AI Accelerators”. AI’s tremendous capability
depends on development and deployment of the lightweight, efficient AI
models that can be executed on resource constrained hardware. The move
towards bigger models requires ever-growing datasets and compute budgets,
which incur massive energy bills over the model deployment lifecycle. It is
crucial to design new AI accelerators/AI hardware (eg: digital
accelerators, custom ASIC design for AI chips, mixed-signal AI chip design,
emerging materials and device technologies for AI systems) that can support
the rapid growth of the models and reduce the overall carbon footprint.
Researchers in this area will have the opportunity to collaborate with
MATRIX researchers with expertise in AI devices, circuit design, and
embedded system design.

Moreover, the successful candidate(s) must demonstrate their ability to
work with and be sensitive to the educational needs of diverse urban
populations and support the University’s commitment to thrive as a¿Hispanic
Serving Institution and a model for student success.
Posting End Date

Review of applications begins December 1st, 2021 and will continue until
the position is filled.
Apply Here
<https://zahr-prd-candidate-ada.utshare.utsystem.edu/psc/ZAHRPRDADA/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_SCHJOB_FL&Action=U>
 Required Application Materials

   1. Curriculum Vitae
   2. Research and teaching statements, which include discussion on the
   role diversity and inclusion plays in an academic environment (3-page
   limit)
   3. Complete contact information for at least three professional
   references

*Please submit all documents together in a single PDF in order to be
considered.*

Questions and nominations for any position should be sent to the Director
of MATRIX AI Consortium, Dhireesha Kudithipudi, Search Committee Chair at
dk at utsa.edu
Required Qualifications

   - Doctorate degree in Computer Engineering, Computer Science, Electrical
   Engineering, and/or related fields.
   - Appropriate research and teaching record for appointment at the rank
   for each position (for those seeking appointments with tenure, this is
   contingent upon Board of Regents’ approval).
   - Demonstrated commitment to inclusion and diversity.
   - Must demonstrate their ability to work with and be sensitive to the
   educational needs of diverse urban populations and support the University’s
   commitment to thrive as a Hispanic Serving Institution and a model for
   student success.

Preferred Qualifications

   - Ideal candidates include those who demonstrate evidence of a
   commitment to collaboration, diversity, equity, and inclusion through
   research, teaching, and service endeavors.
   -  Those who can show a commitment to data-intensive research
   and software reproducibility.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20211005/41a4efa6/attachment.html>