TENURED/TENURE-TRACK PROFESSOR
DEPARTMENT OF STATISTICS & DATA SCIENCES (2020)

Location
Austin, TX

Open Date
October 6, 2020

Application links:
Tenure-Track position (Assistant Professor): apply.interfolio.com/79400
Tenured position (Associate/Full Professor): apply.interfolio.com/79413

Description
The Department of Statistics and Data Sciences at The University of Texas at Austin is seeking applicants for one tenure-track, one tenured, and one open rank faculty position to begin in Fall 2021 subject to the availability of funding. We are interested in filling positions across all ranks (assistant, associate, and full professor).

The successful candidates will be expected to teach undergraduate and graduate statistics and data science courses, have an active research program, supervise graduate students, collaborate with other faculty, and be involved in service to the department, university, and the profession. The department’s teaching load is two courses per year.

The Department of Statistics and Data Sciences currently has 18 tenured and tenure-track faculty with research programs that span statistics, biostatistics, and machine learning and whose associative affiliations encompass biology, business, computer science, medicine, population health, engineering, and mathematics. The department is growing rapidly into a globally recognized center of excellence for research and education in statistical methodology, applied statistics, data science, and machine learning. The department sits amid one of the most intellectually vibrant universities in the country, with abundant opportunities for interdisciplinary research within the College of Natural Sciences and across the LBJ School of Public Affairs, the McCombs School of Business, Dell Medical School, the Oden Institute for Computational Engineering and Sciences, the Population Research Center, the Machine Learning Laboratory which houses the new NSF AI Institute for Foundations of Machine Learning, and many other research entities across the campus. A partnership with the Texas Advanced Computing Center (TACC) provides access to world-class computing resources. The department partners with other computing intensive disciplines through the TEXAS Computing initiative.

The department is dedicated to the goal of building a culturally diverse and pluralistic faculty and staff committed to teaching and working in a multicultural and diverse environment. We are therefore interested in candidates who will contribute to such diversity and equal opportunity in higher education through their teaching, research, and service.

More information about the department is here.

Qualifications
Full consideration will be given to applicants with research interests in any area of statistical applications, theory, or methods and in the emerging field of data science. The minimum qualification is a doctoral degree; strong applicants whose primary degree is not in statistics, biostatistics, machine learning, data science or a related area will also be considered, as long as their research exhibits independence and excellence in one of these areas. Candidates for tenure-track positions are evaluated based on their potential for developing an impactful research program and their ability to demonstrate a serious interest in teaching, mentoring, and service. Candidates for tenured positions are expected to have an internationally-recognized research program and to have demonstrated a strong commitment to excellence in teaching, mentoring, and service.

Application Instructions
Tenure-Track (Assistant Professor): Applicants should submit a cover letter, a CV, a statement of research interests, a teaching statement, and a statement on candidate’s contributions to diversity (optional). In addition, applicants should arrange for three letters of support to be provided under separate cover. Applicants should not submit any supplemental material. However, applicants’ CVs should include links to a web site (or sites) where all papers and software packages listed on the CV can be downloaded.

Tenured (Associate Professor or Professor): Applicants should submit a cover letter and CV. Research statement, teaching statement, and a statement on candidate’s contributions to diversity may be submitted with the application, but are not required at the time of application. Letters of support will be requested on behalf of the finalists for the positions only after permission is granted from the applicant.

The deadline for applications for tenure-track positions is November 30, 2020.

Review of applications for tenured positions will be ongoing until the positions are filled, but applicants are encouraged to apply by December 15, 2020.

The department is committed to respecting the confidentiality of the search process.

Due to the COVID19 pandemic, travel to Austin will not be required as part of the search process. Optional opportunities to visit will be arranged if permissible under university travel guidelines.

A background check will be conducted on applicants selected for the positions.

Questions about the search process should be directed to Professor Cory Zigler (statjobs@austin.utexas.edu), SDS Faculty Search Committee Chair.

Application Process
This institution is using Interfolio’s Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.

Application links:
Tenure-Track position (Assistant Professor): apply.interfolio.com/79400
Tenured position (Associate/Full Professor): apply.interfolio.com/79413

Equal Employment Opportunity Statement
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.