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Assistant, Associate or Full Teaching Professor (LPSOE/LSOE/SR LSOE)-Computational Social Science

Employer
University of California San Diego
Location
La Jolla, California
Closing date
Jan 26, 2022

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Position Type
Faculty
Hours
Full Time
Organization Type
Academic
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Assistant, Associate or Full Teaching Professor (LPSOE/LSOE/SR LSOE) - Computational Social Science, University of California San Diego

The Division of Social Sciences at UC San Diego invites applications for a tenured or tenure- track Teaching Professor position in Computational Social Science, with a start date of July 1st, 2022.

The position: A Teaching Professor is also known within the UC system as a Lecturer with (Potential) Security of Employment (L[P]SOE). The Teaching Professor series parallels that of the research-focused faculty series but with emphasis upon excellence in teaching and other instruction-related activities. Individuals in the position are expected to provide outstanding teaching, as well as to engage in professional and/or scholarly activity and service related to the pedagogical mission of the program and university. This appointment confers membership in UCSD’s Academic Senate. The Teaching Professor series includes security of employment analogous to tenure granted upon promotion to the Associate (LSOE) level; candidates hired at the Associate/LSOE or higher level will be appointed with tenure/security-of-employment. This position will include an appointment in one of the following Computational Social Science affiliated academic departments in the Division of Social Sciences: Anthropology, Cognitive Science, Economics, Ethnic Studies, Linguistics, Political Science, Psychology, Sociology, or Urban Studies & Planning.

The Teaching Professor will contribute to the Computational Social Science program (by teaching introductory courses such as CSS 1, 2, and 100) as well as one specific social science discipline. Our priority is to attract candidates who are strong in relevant technical areas and who can teach Python-based courses on modern computational social science methods at the undergraduate and graduate level. Exceptional candidates will have a track record of teaching relevant courses and either research contributions or completed projects working with computational models and large-scale social science data.

Candidates must have a Ph.D. or ABD in computational social science or a relevant field.

Preference will be given to candidates with:

1. The ability to teach Python-based courses on modern computational social science methods at the undergraduate and graduate level.

2. A track record of scholarly contributions and completed projects working with computational models and large-scale social science data.

3. Ability to teach courses in a specific social science discipline (such as Anthropology, Cognitive Science, Economics, Ethnic Studies, Linguistics, Political Science, Psychology, Sociology, or Urban Studies & Planning).

4. Potential or demonstrated contributions to diversity, equity, and inclusion.

The Division of Social Sciences is committed to academic excellence and diversity within the faculty, staff, and student body. We are thus especially interested in candidates who have strong, demonstrated accomplishments in areas contributing to diversity, equity and inclusion, and a desire to play a leadership role in advancing UC San Diego's commitment to achieving excellence, diversity, and equity within an academic setting.

Salary and starting rank will be commensurate with experience and based on the University of California pay scales.

The position will remain open until filled.

Applications for the Assistant Teaching Professor (LPSOE) position are accepted online at: https://apol-recruit.ucsd.edu/JPF03004

Applications for the Associate or Full Teaching Professor (LSOE/SR LSOE) position are accepted online at: https://apol-recruit.ucsd.edu/JPF03008

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age or protected veteran status.

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