(posted 2021/11/02) Assistant Professor, Tenure-Track, Master of Science in Data Science Program University of San Francisco R0005122 Downtown Campus Job Title: Assistant Professor, Tenure-Track, Master of Science in Data Science Program Job Summary: The Master of Science in Data Science Program (MSDS) at the University of San Francisco invites candidates to apply for a tenure-track Assistant Professor position to begin August 2022, contingent upon funding approval. The MSDS program includes state of the art education in data science and bridges knowledge-to-practice through a 9-month industry practicum that provides students the opportunity to be mentored in solving important data science problems with companies like Amazon, Facebook, Eventbrite, Mozilla, and ZipCar as well as academic groups such as UCSF medicine and Stanford. Faculty in the MSDS program are also supported by the University of San Francisco's Data Institute which exists to strengthen the connection between academia and industry; advance data science research; build and foster an inclusive data science community; and train the next generation of data scientists. Full Job Description: Job Responsibilities: The successful candidate will be expected to teach graduate courses in the Data Science Program, to engage in service to the program and college, and to maintain an active research program that involves students when possible. Close interaction between students, faculty and industry is a hallmark of the Data Science Program. The teaching load is typically two to three half-semester courses per year, plus serving as a practicum mentor to student practicum teams. Duties may also include supporting the undergraduate programs in data science, mathematics and statistics. Minimum Qualifications: Applicants must have a Ph.D. by August 2022 and be working in the fields of analytics, data science, or machine learning. Current faculty have degrees in mathematics, statistics, computer science, and engineering, but we welcome applicants from other disciplines that have retooled as data scientists, such as physicists or biologists. This position requires a commitment to excellence in teaching within a culturally diverse environment. In addition, a strong record of teaching at the university level, evidence of scholarship, and an understanding of and commitment to support the mission of the University of San Francisco are required. The successful candidate must be able to offer their reflections on equity, and strategies for success in engaging with BIPOC students. Applications must be submitted online at https://gnosis.usfca.edu/search/jobs. Applicants should submit a cover letter summarizing interests and qualifications, curriculum vitae, a statement of teaching philosophy and experience, a statement of research plans, evidence of teaching ability (e.g., sample syllabi, teaching evaluations), and three letters of recommendation. Additional materials may be requested later in the process. Questions can be sent to search@datascience.usfca.edu. Review of completed applications will begin on December 15, 2021 and continue until the position is filled. We invite candidates to find out more about the MS Data Science program at https://www.usfca.edu/arts-sciences/graduate-programs/data-science Full-Time/Part-Time: Full time Pay Rate: Salary To apply, visit https://gnosis.usfca.edu/search/jobs. 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 http://www.usfca.edu. Copyright ©2021 Jobelephant.com Inc. All rights reserved. Posted by the FREE value-added recruitment advertising agency jeid-a7d8dab0fb52ef478c85d9a765c75f94 |