MATRIX AI Consortium (University of Texas at San Antonio) is Hiring 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 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 . 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
Required Application Materials
- Curriculum Vitae
- Research and teaching statements, which include discussion on the role diversity and inclusion plays in an academic environment (3-page limit)
- 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 d...@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.
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 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 . 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.
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 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 . 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: Endowed Full Professor with a joint appointment in the Department of Computer Science and the Department of Electrical and Computer Engineering.
Highlighted position: Endowed Full Professor with a joint appointment in the Department of Computer Science and the Department of Electrical and Computer Engineering.
Qualifications
- Inclusive and Human-Centered AI Systems: Outstanding senior candidates are invited for an Endowed Full/Associate professor position in “Inclusive and Human-centered AI Systems”. Human-centered AI, is a multidisciplinary effort to advance AI research and deployment in ways that dramatically amplify human performance in several settings. This area bridges the fields of AI models (eg: explainable AI, fairness in AI models, decentralized decision making, dynamic & adaptive models) with human engagement in high-consequence contexts. Researchers in this area will have the opportunity to collaborate with MATRIX partners in developing convergent AI solutions that are inclusive. Successful candidates will demonstrate (1) a record of high-quality research, publication record, and track-record of external funding in human-centered AI & related areas, (2) excellence in undergraduate and graduate education, and (3) a commitment to inclusion and diversity.
- Inclusive and Human-Centered AI Systems: Outstanding senior candidates are invited for an Endowed Full/Associate professor position in “Inclusive and Human-centered AI Systems”. Human-centered AI, is a multidisciplinary effort to advance AI research and deployment in ways that dramatically amplify human performance in several settings. This area bridges the fields of AI models (eg: explainable AI, fairness in AI models, decentralized decision making, dynamic & adaptive models) with human engagement in high-consequence contexts. Researchers in this area will have the opportunity to collaborate with MATRIX partners in developing convergent AI solutions that are inclusive. Successful candidates will demonstrate (1) a record of high-quality research, publication record, and track-record of external funding in human-centered AI & related areas, (2) excellence in undergraduate and graduate education, and (3) a commitment to inclusion and diversity.
Responsibilities
Responsibilities include research (individual and collaborative), teaching at the graduate and undergraduate levels, and program development. Candidates for the endowed professor/associate professor should be creating research products, expected but are not limited to communicating the research project results in diverse academic outlets; contributing to open-source scientific software, curated datasets, and/or blogs; and developing thought leadership pieces with academic, government, and industry partners.
Responsibilities include research (individual and collaborative), teaching at the graduate and undergraduate levels, and program development. Candidates for the endowed professor/associate professor should be creating research products, expected but are not limited to communicating the research project results in diverse academic outlets; contributing to open-source scientific software, curated datasets, and/or blogs; and developing thought leadership pieces with academic, government, and industry partners.
Posting End Date
All applications received by December 1st, 2021 will be given full consideration. Applications received after that date will be accepted and reviewed until the position is filled.
All applications received by December 1st, 2021 will be given full consideration. Applications received after that date will be accepted and reviewed until the position is filled.
Required Application Materials
Applicants should submit their application packages via the UTSA HR website: https://www.utsa.edu/hr/employment/
Applicants should submit their application packages via the UTSA HR website: https://www.utsa.edu/hr/employment/
- Curriculum Vitae
- Research and teaching statements, which include discussion on the role diversity and inclusion plays in an academic environment (3-page limit)
- Complete contact information for at least three professional references
Please submit all documents together in a single PDF in order to be considered.
- Curriculum Vitae
- Research and teaching statements, which include discussion on the role diversity and inclusion plays in an academic environment (3-page limit)
- 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 d...@utsa.edu.
Questions and nominations for any position should be sent to the Director of MATRIX AI Consortium, Dhireesha Kudithipudi, Search Committee Chair at d...@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)
- 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.
- Demonstrated commitment to inclusion and diversity.
- 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.
- 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.
- The most competitive candidates will also have experience in interdisciplinary research and/or curriculum development, and scientific open-source projects.
- The most competitive candidates will also have experience in interdisciplinary research and/or curriculum development, and scientific open-source projects.
Preferred Qualifications
- Ideal candidates include those who demonstrate evidence of a commitment to collaboration, diversity, equity, and inclusion through research, teaching, service endeavors, and those who can show a commitment to data-intensive research and software reproducibility.
- Ideal candidates include those who demonstrate evidence of a commitment to collaboration, diversity, equity, and inclusion through research, teaching, service endeavors, and those who can show a commitment to data-intensive research and software reproducibility.
Dhireesha Kudithipudi