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Associate/Full Professor in Physics Informed Machine Learning, Fall 2024

Employer
University of Tennessee, Knoxville
Location
Knoxville, Tennessee, United States
Salary
Salary Not Specified
Date posted
Sep 22, 2023

Job Details

Description

The Science Informed Artificial Intelligence (ScAI) cluster at The University of Tennessee, Knoxville seeks exceptional candidates to fill one Open Rank position in Physics Informed Machine Learning, primarily in the Mathematics Department, starting August 1, 2024. 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 11/13/23, and continue until the position is filled. The Knoxville campus of the University of Tennessee is seeking candidates who have the ability to 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 ( T ransdisciplinary AI E ducation and i NN ovation) 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. UTK is a land-grant university and values engaged forms of research/scholarship/creative activity, teaching and service, and considers evidence of these commitments in the records of applicants. 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 centrally located within 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.

For any questions, please contact Professor Xiaobing Feng at xfeng@utk.edu

Qualifications

Minimum Qualifications

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

Preferred Qualifications:

For an appointment at the Full Professor rank:
  • Internationally recognized contributions and leadership in the Mathematics of Machine Learning, especially in the physics informed machine learning.
  • Demonstrated highly strong research publication record.
  • Consistent track record for obtaining funding for the research programs, appropriate for the field of study.
  • Leadership as a PI or co-PI, or participation as a Senior Personnel in interdisciplinary teams supported by an external source.
  • Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students, as well as postdocs.
For an appointment at the Associate Professor rank:
  • Recognized contributions and potential for leadership in the Mathematics of Machine Learning, especially in the model informed machine learning.
  • Demonstrated strong research publication record.
  • Potential for consistent track record for obtaining funding for the research programs, appropriate for the field of study.
  • Potential for leadership as a PI or co-PI, or participation as a Senior Personnel in interdisciplinary teams supported by an external source.
  • Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students, as well as postdocs.
Application Instructions

Applicants who wish to be considered at the Full Professor rank may submit the following materials:
  • Cover letter addressing
    • why this position is of interest.
    • what their vision for this position is.
    • what strategy they will follow to lead these endeavors.
  • Curriculum vitae that includes research mentees at the undergraduate, graduate and postdoc levels.
  • A publication list that states
    • their 5 best articles,
    • all published manuscripts with their mentees as coauthors, and precisely state what level their mentees/coauthors were.
  • 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, as well as underline research leadership initiatives, and iii) collaboration and alignment with the University of Tennessee’s ScAI cluster. In addition, candidates may describe how they would help promote students’ access to and inclusion in their teaching and research.
  • Contact information for three references.
Applicants who wish to be considered at the Associate Professor rank may submit the following materials:
  • Cover letter addressing
    • why this position is of interest.
    • what their vision for this position is.
    • what strategy they will follow to achieve these endeavors.
  • Curriculum vitae that includes research mentees at the undergraduate, graduate or postdoc levels.
  • A publication list that states
    • their 5 best articles,
    • all manuscripts with their mentees as coauthors, and precisely state what level their mentees/coauthors were.
  • 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. In addition, candidates may describe how they would help promote students’ access to and inclusion in their teaching and research.
  • Contact information for three references. Reference letters will be requested after applicants have been short listed.
Materials must be submitted online at http://apply.interfolio.com/132283. For any questions, please contact Professor Xiaobing Feng at xfeng@utk.edu

Equal Employment Opportunity Statement

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. Requests for accommodations of a disability should be directed to the Office of Equity & Diversity, 1840 Melrose Avenue Knoxville, Tennessee 37996-3560 or oed@utk.edu or (865)974-2498. 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 Investigation & Resolution 216 Business Incubator Building 2450 E.J. Chapman Drive Knoxville, Tennessee 37996 or (865)974-0717 or investigations@utk.edu .

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