Associate or Full Professor - Artificial Intelligence Cluster

Associate or Full Professor - Artificial Intelligence Cluster

Location: San Antonio, TX

Regular/Temporary: Regular

Job ID: 12584

Full/Part Time: Full Time

Position Information

Regents Full Professor or Associate Professor

The University of Texas at San Antonio (UTSA), MATRIX AI Consortium, invites applications for the position of Full Professor / Associate Professor, to be appointed as a University of Texas System (UT System) Research Excellence Regents' Professor. Successful candidates will be part of a strategic cluster hiring initiative focused on Artificial Intelligence, with an anticipated start date in the Fall of the 2025-26 academic year.

The University of Texas System recently approved the creation of the Regents' Research Excellence Program across its four Emerging Research Universities (ERUs), including UTSA. UT System has allocated $55 million across all four ERUs to fund the recruitment of research-active faculty to dramatically grow its national research prominence and federal funding opportunities. UTSA's allocation from UT System translates to approximately 40 new faculty positions for new, mid- to senior-level faculty over the next several years who will add expertise in research areas that will enhance competitiveness, help solve societal needs, and advance the university's capacity to meet UT System and state goals as outlined by the Texas Legislature.

UTSA is utilizing our https://www.utsa.edu/strategicplan/initiatives/research/strategic-hiring/ccp/, which is designed to recruit and hire some of the best and brightest minds of varying backgrounds and experiences in select fields to The University of Texas at San Antonio to join in efforts to address some of today's most significant challenges.

For the Artificial Intelligence CCP, the 5 positions open are areas:

• Trustworthy AI/ML Algorithms
• Neuromorphic AI Accelerators/Chips
• Human-Centered AI
• AI Ethics
• Quantum Encryption for AI Confidentiality
The University of Texas at San Antonio (UTSA)

The University of Texas at San Antonio is a Tier One research university and a Hispanic Serving Institution specializing in digital economy, human health, fundamental futures, and social-economic transformation. With more than 35,000 students, it is the largest university in the San Antonio region. UTSA advances knowledge through research and discovery, teaching and learning, community engagement, and public service, and with an intentional focus on career readiness, the university produces more graduates for the workforce than any other institution in the region. It is a catalyst for socioeconomic development and the commercialization of intellectual property — for Texas, the nation, and the world. In August 2024, the https://www.utsa.edu/today/2024/08/story/utsa-and-ut-health-san-antonio-merger-announced.html authorized the UT System to begin integrating UTSA and the UT Health Science Center at San Antonio into one unified institution, establishing a world-class university that integrates academic, research, and clinical excellence to build a profoundly impactful university of the future. Driven by a vision for growth and impact, this merger will expand the capacity to offer robust undergraduate and graduate programs, attract top-tier faculty and staff, develop innovative initiatives, and elevate transdisciplinary research to address the evolving needs of the region.

UTSA has been recognized as a Top Employer in Texas by Forbes Magazine. Learn more https://www.utsa.edu/, on https://www.utsa.edu/today/ or on https://twitter.com/utsa, https://www.instagram.com/utsa/, https://www.facebook.com/utsa, https://www.youtube.com/user/utsaor https://www.linkedin.com/school/the-university-of-texas-at-san-antonio/?lipi=urn%3Ali%3Apage%3Ad_flagship3_university_admin%3BFcmdPCevQ7ebJE1xpIJlRw%3D%3D.

The Regents Professors will be core members of the MATRIX Consortium, which is a central hub for 87 AI scientists, facilitating transdisciplinary research, fostering high-impact collaborations, and offering thought leadership and domain expertise to address the most challenging and complex problems in AI. Areas of interest include Trustworthy AI/ML Algorithms, Neuromorphic AI Accelerators, Human-centered AI, AI Ethics, all of which advance the research thrusts in the MATRIX. MATRIX strives for scientific excellence in developing holistic solutions for human well-being. The team has a successful track record in large collaborative grants that generated multiple centers, such as the NSF AI Partner Institute, two NSF EFRI BRAIDs, AFOSR COE in neuro-inspired AI, along with centers and large collaborative projects in AI for healthcare. UTSA is also home to multiple large DOD initiatives in the national security and cybersecurity domains, such as the NSCC and CyManII. There will also be opportunities to collaborate with several of these large initiatives.

Position Summary

Highlighted position(s):

• Trustworthy AI/ML Algorithms: Associate or Full Professor (Joint Appointment with Departments of CS/ECE). Advances in machine learning alongside computer vision, natural language processing, and knowledge reasoning are germane to advancing and sustaining the applied domains of AI. Given the human-centered nature of these applications, AI/ML techniques need to be robust against adversarial threats and manipulations (of data and models) and must include security and privacy guarantees, depending on the context in which they operate. There is significant research interest and activity, ranging from robust, secure, and explainable AI/ML systems that are resilient against malicious threats and manipulations, offer end-user privacy, and generate trustworthy outcomes.
• Neuromorphic AI Accelerators/Chips: Associate or Full Professor (Joint Appointment with Departments of ECE/NDRB/BME) The future of sustainable AI depends on the ability to design and deploy models and systems that can be executed on resource constrained devices. MATRIX is interested in recruiting a researcher who tackles these problems using neuromorphic approaches. Areas of interest are neuro-inspired AI accelerators, mixed-signal accelerators, digital accelerators, analog processors, memristor circuits and architectures, and other emerging device-based neuro-inspired architectures.
• Human-Centered AI: Associate or Full Professor (Joint appointments within Departments of BME/SA+P/NDRB/Medical school) Human-centered AI is a key to developing AI that augments human wellbeing and performance. This area includes AI applications to solving biomedical problems, AI-driven robotics, real-time decision-making systems for clinical care, brain-machine pairings, effective computing, trust, control, and transparency in human-AI partnerships, and human-centered designs that are biologically inspired.
• AI Ethics: Associate or Full Professor (Joint Appointment with Departments of Philosophy and new college) AI technologies such as generative models are highly capable but also come with ethical challenges such as 1) biases in datasets, algorithms, and applications; (2) issues related to identifiability and privacy; (3) impacts on disadvantaged or marginalized groups; (4) health disparities; (5) political abuse of AI systems and technology, and (6) potential adverse social, individual, and community consequences of research, development, and widespread use. We are interested in transdisciplinary applicants who can tackle present and emerging AI ethical problems and that can effectively and actively collaborate with other members of the MATRIX AI consortium.
• Quantum Encryption for AI Confidentiality: Associate or Full Professor (CS/ECE and Joint Appointment with Math Department) Generative AI technologies such as large language models (LLMs) are increasingly operationalized across various industries but face unprecedented adversarial threats, including 1) the risk of backdooring thru model knowledge editing, 2) model inversion attack that compromise privacy 3) exploitation of models for malicious purposes such as malware creation 4) the need for robust defenses of model parameters, such as AI Quantum Encryption.
Required qualifications:

The required qualifications of the successful candidates are:

• A doctorate degree in Computer Engineering, Computer Science, Biomedical Engineering, Electrical Engineering, Neuroscience, Philosophy, 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).
• Must demonstrate their ability to work with and be sensitive to the educational needs of 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 large-scale research engagements.

Preferred qualifications:

• Ideal candidates are those who demonstrate a strong commitment to collaboration across multiple disciplines in research, teaching, service, and open-source initiatives.

To view the full job posting and apply for this position, go to https://apptrkr.com/6020283

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