APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.

• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.

• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

 

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

 

POSITION SPECIFICS

The Institute for Computational and Data Sciences (ICDS) at Penn State University is hiring multiple Tenure-track or Tenured faculty as part of the second year of an ambitious multi-year cluster hire in AI across multiple university campuses. These faculty will complement a strong cohort of over 30 existing AI faculty plus many more whose work leverages AI to advance the sciences and engineering.

The focus of this year’s search is on faculty with expertise in AI + Materials, AI + Health, and Foundations of AI. Ideal candidates’ research will focus on AI + X, meaning faculty who advance AI methods to solve scientific problems in different disciplines (X), rather than X + AI, where faculty use existing methods.

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. As a joint appointment, successful candidates will be expected to contribute to both their tenure home units and to ICDS.

Faculty members in these positions will be expected to develop nationally recognized research programs, contribute to excellence in education, and engage in collaborative, interdisciplinary scholarship. The tenure home and specific requirements will be based on the specific position(s) applied for and the successful candidate’s expertise.

Applicants should submit a single PDF through the application portal containing the following materials in this order: cover letter, teaching statement, research statement, the names and contact information for four references, and their curriculum vitae. The cover letter should explicitly specify the area(s) and department(s) to which the applicant is applying (see below for information about calls for each department).

Applicant review will begin in October 2026. For full consideration, please submit applications no later than December 7, 2026.

For Questions, contact ICDS director Guido Cervone ([email protected]).

Penn State Academic Ranks Defined:

Assistant professors should show early promise in teaching or research through emerging scholarly or professional contributions. Associate professors should have a record of high-quality publications and demonstrate teaching excellence in their field. Full professors should demonstrate a distinguished record of advanced work and leadership, reflecting established excellence in teaching, mentoring, and/or research.

AI + Materials

• Department of Materials Science and Engineering, College of Earth and Minerals Science, University Park, PA: An Assistant, Associate, or Full Professor whose research and teaching advance interdisciplinary materials science by adopting advanced methods in artificial intelligence (AI), machine learning (ML), and data-driven research to generate new fundamental science and accelerate materials innovation. The research will be accompanied by department service and teaching that reflects both ML/AI approaches and the traditional tenets of Materials Science and Engineering. The successful candidate will develop, manage, and sustain an active extramurally funded research program; participate in service activities within the departmental, college, university, and professional society domains; and excel in teaching at the graduate and undergraduate levels. The department seeks to accelerate and streamline the discovery, development, and understanding of novel materials by incorporating machine learning, artificial intelligence, and data-driven research approaches with established experimental and computational methods. Candidates must possess a Ph.D. in Materials Science and Engineering, Physics, Chemistry, Mechanical Engineering, Chemical Engineering, or a closely related discipline before their appointment start date at Penn State.

• School of Engineering, Penn State Behrend, Erie, PA AI + Polymers: An Assistant, Associate, or Full Professor whose research and teaching advance novel artificial intelligence and machine learning methodologies motivated by challenges in polymer materials, polymer informatics, plastics manufacturing, intelligent manufacturing, digital twins, and AI-enabled characterization. The successful candidate will establish an internationally recognized, externally funded research program that develops novel AI methodologies motivated by engineering materials and manufacturing challenges; teach undergraduate and graduate courses; mentor undergraduate and graduate researchers; collaborate across Penn State through the Institute for Computational and Data Sciences (ICDS), the Materials Research Institute, and related interdisciplinary initiatives; engage with industry through the Behrend Open Lab and the Center for Manufacturing Competitiveness (CMC); and contribute to service within the school, university, and profession. The anticipated tenure home for this position is the Department of Computer Science and Software Engineering (CSSE), with strong interdisciplinary collaborations with faculty in polymers, materials, and manufacturing across the School of Engineering. This position is one of two complementary faculty hires that together will establish the Penn State Behrend AI + Materials Cluster. The successful candidate will work closely with the companion AI + Metals faculty member to create a collaborative research community focused on AI-enabled engineering materials manufacturing. The department desires to advance research with the philosophy that polymers are not simply an application domain, but a rich scientific and engineering driver for advancing artificial intelligence itself. The successful candidate will leverage Behrend's strengths in manufacturing, industry engagement, and experiential learning to pursue transformative research, build interdisciplinary collaborations, and create exceptional opportunities for undergraduate and graduate students. Candidates must possess a Ph.D. in Polymer Engineering, Materials Science and Engineering, Chemical Engineering, Mechanical Engineering, Computer Science, Artificial Intelligence, Data Science, Industrial Engineering, or a closely related discipline before their appointment start date at Penn State.

• School of Engineering, Penn State Behrend, Erie, PA AI + Metals: An Assistant, Associate, or Full Professor whose research and teaching advance novel artificial intelligence and machine learning methodologies motivated by challenges in metallurgy, metal materials, additive manufacturing, computational materials science, intelligent manufacturing, digital engineering, and AI-enabled quality assurance. The successful candidate will establish an internationally recognized, externally funded research program that develops novel AI methodologies motivated by engineering materials and manufacturing challenges; teach undergraduate and graduate courses; mentor undergraduate and graduate researchers; collaborate across Penn State through the Institute for Computational and Data Sciences (ICDS), the Materials Research Institute, and related interdisciplinary initiatives; engage with industry through the Behrend Open Lab and the Center for Manufacturing Competitiveness (CMC); and contribute to service within the school, university, and profession. The anticipated tenure home for this position is the Department of Computer Science and Software Engineering (CSSE), with strong interdisciplinary collaborations with faculty in metals, materials, and manufacturing across the School of Engineering. This position is one of two complementary faculty hires that together will establish the Penn State Behrend AI + Materials Cluster. The successful candidate will work closely with the companion AI + Polymers faculty member to create a collaborative research community focused on AI-enabled engineering materials manufacturing. The department desires to advance research with the philosophy that metals are not simply an application domain, but a rich scientific and engineering driver for advancing artificial intelligence itself. The successful candidate will leverage Behrend's strengths in manufacturing, industry engagement, and experiential learning to pursue transformative research, build interdisciplinary collaborations, and create exceptional opportunities for undergraduate and graduate students. Candidates must possess a Ph.D. in Materials Science and Engineering, Metallurgical Engineering, Mechanical Engineering, Manufacturing Engineering, Industrial Engineering, Computer Science, Artificial Intelligence, Data Science, or a closely related discipline before their appointment start date at Penn State.

AI + Health

• School of Science, Engineering and Technology (SSET), Penn State Harrisburg, Middletown, PA: An Assistant or Associate Professor whose research and teaching advance the development and/or implementation of AI and technology to improve health outcomes in isolated and/or vulnerable populations. The successful candidate will be expected to teach undergraduate and graduate courses in the department of appointment plus interdisciplinary courses in artificial intelligence, health technology, biomedical systems, or related program areas of SSET. In research, the successful candidate will address challenges in healthcare access, delivery, diagnosis, or treatment, with particular attention to rural communities, older adults, and other populations with limited access to care. Examples of relevant research may include using AI to enhance remote access to health care professionals and diagnostic services, timely diagnostics, improved environments for living and working, or collecting long-term patient data to enhance whole-patient evaluation. They will be expected to collaborate with one or more Penn State Harrisburg and SSET research initiatives: Smart Homes, Smart Medical Technology prototyping, AI Innovation, and appropriate departments in the College of Medicine. They will be expected to be an active member of ICDS and provide service to the school, college, and profession. The school aims to harness the potential of AI in health care engineering to improve the quality and timeliness of care to isolated and vulnerable populations. Candidates must possess a PhD in Artificial Intelligence, Computer Science, Mechanical Engineering, Electrical Engineering, Civil Engineering, Environmental Engineering, or a closely related discipline before their appointment start date at Penn State.

• College of Medicine, Hershey, PA: An Assistant, Associate, or Full Professor level scholar to apply world-class computing and AI anchored in real-world reality to answer key health questions in basic, translational, and/or clinical sciences. Researchers will be expected to make real-world impacts on health to address important questions in biomedicine, disease prevention, improved medical/behavioral treatments, diagnostics, drug safety, and effective health care delivery. The College seeks to expand leadership in strategic priorities such as rural health, aging, cancer, cardiovascular, neurological, immunological, and maternal and child health, while leveraging Penn State’s strengths in interdisciplinary and translational research, biomedical informatics, basic sciences, and population health sciences. Applicants at the Associate or Full Professor level should have an established externally funded research program. Candidates must possess an MD and/or PhD in Artificial Intelligence, Health Data Science, Computational Biology, Bioengineering, Clinical Informatics, Translational Science, Public Health with a computational focus, or a closely related discipline before their appointment start date at Penn State.

• Department of Statistics, Eberly College of Science, University Park, PA: An Assistant Professor in Statistics with a research emphasis on AI and Machine Learning for health data science, with applications in areas such as neuroscience, environmental health, and the social determinants of health. The successful candidate will contribute to interdisciplinary research in health analytics and develop new statistical and computational methodology at the interface of AI, population health, and societal impact. Applicants will be expected to develop an independent research program and will contribute to the department’s and college’s teaching and service mission. Competitive applicants for the rank of Assistant Professor must possess a Ph.D. (or equivalent terminal degree) in Statistics, Biostatistics, Bioinformatics, Data Science, Machine Learning, or a closely related field before their appointment start date at Penn State.

• College of Health and Human Development, University Park, PA: An Assistant, Associate, or Full Professor whose research and teaching advance our understanding of how AI can be leveraged in the design, adaptation, and implementation of interventions to improve health outcomes and/or leverage AI to help integrate these interventions into clinical and population health practice. The successful candidate will help expand our understanding of AI and translate that knowledge into evidence-based, sustainable practices that enhance health and well-being. The college seeks to complement existing areas of strength, including but not limited to: physical activity, cognitive health, substance abuse, healthy eating, weight regulation, sleep, stress management, language and communication disorders, and/or the management of chronic diseases associated with these areas. There is the potential to hire multiple candidates under this initiative, and successful hires will be placed in the appropriate department based on their area of research (e.g., Biobehavioral Health, Communication Sciences and Disorders, Human Development and Family Studies, Kinesiology, Nutritional Sciences). Candidates must possess a PhD in an aligned or closely related discipline before their appointment start date at Penn State.

• Department of Informatics and Intelligent Systems, College of Information Sciences and Technology, University Park, PA: An Assistant, Associate, or Full Professor whose research and teaching advance innovative artificial intelligence methods for health and biomedicine. The successful candidate will establish an externally funded research program; develop new AI methods for electronic health records, biomedical images and videos, genomic and multi-omics data, physiological signals, or other multimodal health data; teach undergraduate and graduate courses in artificial intelligence, data science, biomedical informatics, or related areas; mentor students and postdoctoral scholars; collaborate with computational researchers, biomedical scientists, clinicians, and health-system partners; and contribute to departmental, college, university, and professional service. The college aims to strengthen Penn State’s leadership in AI + Health by connecting foundational and methodological advances in AI with important problems in diagnosis, prognosis, precision medicine, computational biology, medical informatics, and human health. Candidates must possess a PhD in Information Science, Computer Science, Data Science, Artificial Intelligence, Biomedical Informatics, Bioinformatics, Computational Biology, Electrical and Computer Engineering, Statistics, Applied Mathematics, or a closely related discipline before their appointment start date at Penn State.

Foundations of AI

• Department of Informatics and Intelligent Systems, College of Information Sciences and Technology, University Park, PA: An Assistant, Associate, or Full Professor whose research and teaching advance the foundations of artificial intelligence. The successful candidate will establish an externally funded research program; develop fundamental methods in one or more areas such as machine learning, generative AI, foundation models, physical or embodied AI, trustworthy and privacy-preserving AI, explainable and human-centered AI, or socially responsible AI; teach undergraduate and graduate courses in artificial intelligence, machine learning, data science, and related areas; mentor students and postdoctoral scholars; collaborate across disciplinary and institutional boundaries; and contribute to departmental, college, university, and professional service. The department seeks to strengthen Penn State’s leadership in foundational AI while creating methodological advances that support responsible innovation and scientific discovery across disciplines. Candidates must possess a PhD in Information Science, Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical and Computer Engineering, Robotics, Statistics, Applied Mathematics, or a closely related discipline before their appointment start date at Penn State.

• Department of Mathematics, Eberly College of Science, University Park, PA: An Assistant or Associate Professor whose research and teaching advance the mathematical foundations of AI. This includes, but is not limited to, mathematical contributions to learning theory, information geometry and geometric deep learning, uncertainty quantification and probabilistic methods, and integrating any area of mathematics research and AI. The successful candidate will be expected to develop a leading research program, contribute to undergraduate teaching and commit to teaching excellence, collaborate across campus on AI initiatives when appropriate, and contribute to a positive departmental environment, including our departmental strategy for AI. Our current faculty’s research includes AI methods in: Life Sciences and Health, Scientific Machine Learning, Operator Learning, Geometric & Topological Data Analysis, Quantum Computing, Number Theory, and Formal proofs. Applicants will be expected to develop an independent research program and will contribute to the department’s and college’s teaching and service mission. Applicants seeking the rank of Associate Professor should have the same qualifications as the rank of Assistant Professor, as well as a strong track record of scholarly achievement, external funding, and demonstrated success in teaching and service. Competitive applicants for the rank of Assistant Professor must possess a Ph.D. (or equivalent terminal degree) in Mathematics or a closely related discipline before their appointment start date at Penn State.

 

BACKGROUND CHECKS/CLEARANCES

 

 

 

BENEFITS

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional wellbeing. In addition to comprehensive medical, dental, and vision coverage, employees enjoy robust retirement plans. One of the standout benefits is the generous 75% tuition discount, available to employees as well as eligible spouses and children.

 

For more detailed information, please visit our Benefits Page. (Note: For Postdoctoral benefits, please see our Postdoctoral Benefits page.)

 

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.

Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university’s teaching, research, and service mission.

 

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