University of Tennessee, Mathematics

Position ID: UTK-ASSOC [#22104]
Position Title: Associate Professor, Physics Informed Machine Learning
Position Type: Tenured/Tenure-track faculty
Position Location: Knoxville, Tennessee 37996-1320, United States [map] sort by distance
Subject Area: Science Informed Artificial Intelligence (ScAI)
Application Deadline: 2023/08/18 11:59PMhelp popup finished (2023/02/13, finished 2024/02/24, listed until 2023/08/18)
Position Description:    

*** this position has been closed. ***

The Science Informed Artificial Intelligence (ScAI) cluster at The University of Tennessee, Knoxville seeks exceptional candidates to fill one position at the Associate Professor level, primarily in the Mathematics Department, starting August 1, 2023. There will also be a unique opportunity for a joint appointment at the Chemistry, Industrial Systems Engineering, Mechanical Aerospace and Biomedical Engineering, or Physics departments.

Review of applications will begin on Wednesday 3/15/23, and continue until the position is filled. The University of Tennessee encourages applications from candidates who can contribute in meaningful ways to the diversity and intercultural goals of the University.

The ScAI cluster is part of the “It takes a Volunteer” cluster hiring initiative at the University of Tennessee Knoxville. https://provost.utk.edu/it-takes-a-volunteer-2023-2025-cluster-hiring-initiative/ The ScAI will be a cluster team of excellence in the science, mathematics, and optimization of AI for advancing scientific and engineering applications and offer a direct impact on additive manufacturing and hypersonics defense systems. As part of this institutional priority initiative, new hires will join a dynamic core group of scientific collaborators with complementary experience and a shared interest in building a national reputation for excellence and innovation in ScAI. In addition, clusters are expected to work together to grow the University’s reputation in ScAI through shared grant proposals, publications, and innovative new curricular programming.

The new hires will also support and contribute to the AI TENNessee (Transdisciplinary AI Education and iNNovation) Initiative. The AI TENNessee Initiative is a new research and education initiative focused on the State of Tennessee’s unique AI strengths and opportunities. Led by the University of Tennessee, Knoxville, this initiative is engaging with academic, industry, and community partners across Tennessee to leverage the benefits of AI across all disciplines and economic sectors in areas such as AI for science, smart manufacturing, climate-smart agriculture and forestry, precision health and environment, and future mobility. Our goal is to improve lives through AI research and education. The mission of the AI TENNessee initiative is to: 1) advance cutting-edge fundamental and transdisciplinary AI research and creative activity across all disciplines to address important challenges; 2) expand the number of Tennessee students developing skills and core competencies in AI across many disciplines to prepare them for AI-enabled jobs of today and the future; and 3) partner with industry and institutions statewide to position Tennessee as a national and global leader in the data-intensive knowledge economy.

The University of Tennessee Knoxville is the flagship university in the Tennessee state higher education system. The state of Tennessee is in solid fiscal condition, and the University has provided salary increases since 2010 (except for 2020 during the pandemic). Knoxville is a vibrant and diverse medium-sized city located within easy driving distance to Ashville, Nashville, Atlanta, and the Great Smoky Mountains. It has a beautiful and walkable downtown, varied nightlife, eclectic shopping and restaurants, and relatively low cost of living.

Qualifications Minimum Qualifications

A PhD or equivalent degree in mathematics, applied mathematics, or statistics is required.

To be eligible for appointment as an associate professor, the selected candidate must have a demonstrated record of teaching, research, and service commensurate with a faculty appointment at that rank.

Preferred Qualifications:

Highly recognized contributions and leadership in the Mathematics of Machine Learning, especially in Physics Informed Machine Learning. Demonstrated strong research publication record. High potential to initiate and obtain funding for the research programs, appropriate for the field of study. Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students, as well as postdocs. Application Instructions Required Application Materials:

Cover letter addressing why this position is of interest. Curriculum vitae that includes research mentees at the undergraduate, graduate and postdoc levels. A publication list that highlights research with mentees. A list of funding record, including the total dollar amount per grant/collaborative agreement and the direct dollar amount allocated to the applicant’s research group. A statement of professional goals highlighting i) teaching and mentoring, ii) research both disciplinary and transdisciplinary, and iii) collaboration and alignment with the University of Tennessee’s ScAI cluster. A diversity equity and inclusion statement is encouraged. Contact information for three references.

All qualified applicants will receive equal consideration for employment and admission without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, genetic information, veteran status, and parental status, or any other characteristic protected by federal or state law. In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, the University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends to employment by the university. Inquiries and charges of violation of Title VI (race, color, and national origin), Title IX (sex), Section 504 (disability), the ADA (disability), the Age Discrimination in Employment Act (age), sexual orientation, or veteran status should be directed to the Office of Equity and Diversity, 1840 Melrose Avenue, Knoxville, TN 37996-3560, telephone 865-974-2498. Requests for accommodation of a disability should be directed to the ADA Coordinator at the Office of Equity and Diversity.


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Contact: Vasileios Maroulas, 865-974-2463, 865-974-6576 (fax)
Email: email address
Postal Mail:
University of Tennessee
Department of Mathematics
1403 Circle Drive/ 227 Ayres Hall
Knoxville TN 37996-1320
Web Page: https://math.utk.edu/