University of San Francisco, Department of Mathematics and Statistics

Position ID:University of San Francisco-Department of Mathematics and Statistics-APTTMS [#20351]
Position Title: Assistant Professor, Tenure-Track, Mathematics and Statistics / M.S. in Data Science
Position Type:Tenured/Tenure-track faculty
Position Location:San Francisco, California 94117, United States
Subject Areas: Statistics
Appl Deadline: finished (2021/11/01, finished 2023/05/06, listed until 2022/11/01)
Position Description:    

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Assistant Professor, Tenure-Track, Mathematics and Statistics / M.S. in Data Science

University of San Francisco


USF Hilltop Campus

Job Title:
Assistant Professor, Tenure-Track, Mathematics and Statistics / M.S. in Data Science

Job Summary:
The Department of Mathematics and Statistics at the University of San Francisco invites applications for a tenure-track Assistant Professor position to begin August 2022, contingent upon funding approval. We seek well-qualified candidates in the areas of applied mathematics or statistics, with a focus on the extraction of knowledge from data. Special consideration will be given to candidates who can directly contribute to both the interdisciplinary bachelor's degree in data science (BSDS), as well as the master's program in data science (MSDS).

The MSDS program is a fast-paced, one-year program which prepares students for careers in data science. MSDS students complete a 9 month industry practicum project as part of the program.

Full Job Description:

Job Responsibilities: The successful candidate will be expected to teach undergraduate and graduate courses and mentor students who work with our industry partners. The teaching load for this position is usually two four-unit courses per semester. In addition, the successful candidate will be expected to engage in service to the department(s) and college, as well as maintain an active research program that engages students when possible.

Minimum Qualifications: Applicants must have a Ph.D. earned by August 2022 in mathematics, statistics, or a related field. The position requires a commitment to excellence in teaching within a culturally diverse environment, and a strong research program with potential for student engagement. The successful candidate must be able to offer their reflections on diversity, equity, and inclusion (DEI) and discuss how they would engage with and enhance the department's and college's efforts in this area.

Candidates should submit a letter of application, curriculum vitae, statements of teaching philosophy and research plans, a statement on diversity, equity, and inclusion (which may include your thoughts and/or experiences concerning equitable education for underserved and marginalized communities, your commitment to or experience with broadening participation in the field, experience working on a diverse team, and/or experience working with different communication/learning styles), teaching evaluations, graduate transcripts, and three letters of recommendation. All of the above elements are required to complete your application. Preliminary interviews will be conducted in January 2022 by videoconference.

Completed applications must be submitted online at For full consideration, applications should be received by December 10, 2021. We invite candidates to find out more about our department at and information about the Data Science Major can be found at The graduate program can be found at Questions regarding this search may be emailed to

Full time

Pay Rate:

To apply, visit :

The University of San Francisco is located in the heart of one of the world's most innovative and diverse cities, and is home to a vibrant academic community of students and faculty who achieve excellence in their fields. Its diverse student body enjoys direct access to faculty, small classes and outstanding opportunities in the city itself. USF is San Francisco's first university, and its Jesuit Catholic mission helps ignite a student's passion for social justice and a desire to “Change the World From Here.” For more information, visit

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