Penn State University is aiming to hire multiple Tenure-track or Tenured faculty as part of an ambitious multi-year cluster hire in AI across the university, to help realize the university’s goals of transformative integration of AI across research and graduate and undergraduate curricula across all disciplines. These faculty will complement a strong cohort of over 30 existing faculty in AI and many more whose work leverages AI to advance sciences and engineering. The university has launched two new undergraduate degree programs – in AI methods and Applications (offered by the College of Information Sciences and Technology), and in AI Engineering (offered by the College of Engineering).
The focus of the search this year is on faculty with expertise in AI Foundations and Methods or in the integration of AI into Sciences, Engineering, Healthcare, and Education and Workforce Development. The successful candidates will join a vibrant, interdisciplinary research community at Penn State and will have collaborative opportunities and access to extensive resources offered by the interdisciplinary research institutes – Institute for Computational and Data Sciences (which provides excellent high-performance computing facilities), Materials Research Institute, and the Clinical and Translational Sciences Institute. Faculty members in these positions will be expected to develop nationally recognized research programs, contribute to excellence in graduate and undergraduate education, and engage in collaborative, interdisciplinary scholarship. In addition, the successful candidates will teach and mentor students and collaborate to develop courses that integrate AI into research and curricula in their respective fields.
Candidates must indicate in their application one or more Departments they wish to apply to. For questions, contact ICDS director Guido Cervone (icds@psu.edu).
AI Foundations and Methods
We seek faculty whose primary expertise is in core areas of AI, with a strong track record or interest in applications of AI in sciences or engineering.
Department of Computer Science, College of Engineering
An Assistant, Associate, or Full Professor whose research and teaching advance core AI and ML theory, foundation models and generative AI, reinforcement learning and autonomous agents, hardware and systems for AI, edge and federated learning, AI security and privacy, quantum machine learning (QML), robotics, and AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease modeling, materials, and biomanufacturing).
Department of Informatics and Intelligent Systems, College of Information Science and Technology
An Assistant, Associate, or Full Professor whose research and teaching advance core areas of AI, including, but not limited to, generative AI, neuro-symbolic AI, neuromorphic AI, embodied AI, multi-agent AI, human-centered AI, quantum AI, and/or transformative AI applications. Of particular interest are candidates who combine core AI expertise with a demonstrated track record of applications in AI-powered scientific discovery (in physical sciences, life sciences, health sciences, materials sciences) or in critical infrastructure, security, public policy, humanities and social sciences.
Department of Computer Science and Software Engineering, School of Engineering, Penn State Behrend
An Assistant Professor whose research and teaching advance the science and engineering of AI and its integration into intelligent, autonomous, or data-driven systems. Areas of interest include—but are not limited to machine learning and deep learning architectures; trustworthy or explainable AI; generative AI and natural-language systems; computer vision and multimodal perception; distributed and embedded AI for edge or cloud environments; AI-enabled software engineering and adaptive systems. Opportunities exist for collaboration across Penn State’s AI network and within Behrend’s applied-research ecosystem—including the Center for Manufacturing Competitiveness, the Sustainable Plastics and Materials Laboratories, the Robotics and Automation Lab, and the Virtual/Augmented Reality Innovation Lab)—which serve as regional and national testbeds for AI-driven technologies.
AI for Materials Science and Engineering
AI is transforming both materials science and chemical engineering by enabling smarter, faster, and more efficient solutions to complex scientific and technological challenges. From optimizing reaction conditions and process control to accelerating materials discovery, AI and machine learning (ML) offer powerful tools for uncovering hidden patterns in experimental and computational data, predicting properties and performance, and guiding decision-making with unprecedented precision. Together, these approaches are driving innovation in key areas including sustainability, catalysis, biotechnology, energy systems, and advanced materials. These positions will be jointly managed by the Institute for Computational and Data Sciences and the Materials Research Institute (https://www.mri.psu.edu/)
Department of Chemical Engineering, College of Engineering
An Assistant Professor whose research and teaching advance the integration of AI/ML with chemical engineering to accelerate materials discovery and production. The successful candidate will contribute to interdisciplinary collaborations that leverage AI/ML for process optimization, predictive modeling, and data-driven decision-making in chemical systems. We seek to recruit faculty whose work bridges computational methods with experimental and theoretical approaches to address complex challenges in chemical engineering.
Department of Materials Science and Engineering, College of Earth and Mineral Sciences
An Assistant Professor whose research and teaching advance AI-driven materials discovery and processing. The successful candidate will develop and implement innovative machine learning methods for materials research and integrate data-driven approaches into undergraduate and graduate curricula to enhance student success.
AI for Rural Health
Pennsylvania is in the top 3 states in the United States in terms of rural populations. Rural populations face increased morbidity and mortality from leading causes of death, driven by lower insured rates and socioeconomic status, and less education and healthy behaviors. As part of its land-grant mission, Penn State is looking for faculty who can help transform and advance health care for rural populations. These positions will be jointly managed by the Institute for Computational and Data Sciences and the Penn State Clinical and Translational Science Institute.
College of Medicine
An Assistant Professor whose research and teaching advance the intersection of basic, translational, and/or clinical sciences, with a focus on AI for rural health, to enhance access, care delivery, and health equity in rural and medically underserved populations. We seek to recruit faculty whose research bridges AI methodology and clinical or translational applications to address one or more of the most important questions in health care, medical/behavioral treatment, disease prevention, and environmental safety by applying the best of emerging computing and AI. These areas align closely with the NIH’s strategic priorities, such as addressing aging, health disparities, and child health, while leveraging the university’s strengths in translational research, biomedical informatics, and population health sciences.
College of Nursing
An Assistant, Associate, or Full Professor whose research and teaching advance the intersection of nursing, AI, and rural health. The successful candidate will contribute to the College’s mission to transform care delivery and harness emerging technologies through interdisciplinary collaborations that improve outcomes in underserved rural communities. We seek to recruit faculty to address one or more of the most important questions, including AI-driven decision support in nursing practice, predictive analytics for rural population health, telehealth, telenursing, and remote monitoring for geographically isolated populations, human-centered design of intelligent health systems for rural care delivery, and ethical, social, and policy implications of AI in rural healthcare.
Penn State Harrisburg, School of Science, Engineering and Technology
An Assistant Professor whose research and teaching advance engineering (mechanical, civil, electrical, or environmental) and/or computer science, focusing on artificial intelligence in support of medical and health-related rural health research. This position is part of a cluster hire within the Smart Cities and Smart Home Research Initiatives and will collaborate closely with the Penn State College of Medicine and partners across the Commonwealth. Areas of emphasis include smart and digital manufacturing, AI in manufacturing and health systems, and human–system integration, including virtual and augmented reality environments. The successful candidate will engage in interdisciplinary research that connects engineering innovation, computing, and health technologies to address complex societal challenges through applied AI. The position offers access to collaborative research facilities, including the Smart Home Innovation Lab and Medical Prototyping Hub, fostering partnerships that connect academia, industry, and health research.
AI in Education for Workforce and Creative Industries
As AI tools are already being deployed at scale in formal and informal learning environments, workforce training programs, and creative studios worldwide—often without adequate pedagogical research or ethical frameworks—this cluster addresses the most immediate and far-reaching impact of AI on society: how millions of people learn, work, and create. We seek to hire faculty who advance the application of AI technologies in teaching, learning, workforce development, and the creative industries to influence innovation, leadership, and policy around the integration of AI across all areas of human endeavor. Successful candidates will advance research and creative practice that connect artistic expression, learning, and human development through emerging AI technologies.
School of Music, College of Arts and Architecture
An Assistant Professor whose research/creative practice advances and connects musical expression, learning, and human development through emerging AI technologies. This position will explore how AI can transform musical practice and learning—from generative musical composition and interactive performance systems to new modes of sonic exploration and musical expression. It investigates fundamental questions about musical cognition and how humans create and communicate through sound. This work would also examine how machine learning approaches can deepen our understanding of musicality, music learning, and creativity. The appointment bridges music, education, and technology, while aligning with national priorities in AI for learning, ethics, and workforce development. Potential areas of emphasis include: AI-assisted composition, performance, and pedagogy; Generative systems for sound, storytelling, and creative learning; Human-AI co-creativity and adaptive learning systems in the arts; Immersive and adaptive simulation environments for music education and music pedagogy using LLMs and VR/AR; and, Ethical, accessible, and equitable applications of AI in creative and artistic professional training contexts.
College of Education
An Assistant Professor whose research advances AI and STEM education to promote human-AI collaboration, adaptive learning, and creative problem-solving. The successful candidate will contribute to the design of human-centered adaptive learning systems, immersive simulations using LLMs and VR/AR, and AI-enabled career pathways across disciplines. Potential areas of emphasis include: AI-enhanced STEM pedagogy and curriculum; Adaptive learning systems and intelligent tutoring; Human-AI collaboration in STEM innovation; Immersive simulations for interdisciplinary workforce training; Predictive analytics for student success; Integration of advanced AI technologies such as machine learning, natural language processing, and digital twins into curriculum and training programs; and, Ethical, equitable, and inclusive AI applications in education and career pathways. This position will expand externally funded research, support interdisciplinary initiatives, and help shape educational impact, leadership, and policy in response to AI’s growing role in STEM workforce development.