How to Apply
A cover letter is required for consideration for this position. The cover letter should address your specific interest in the position and outline skills and experience in teaching quantitative methods that directly relate to this position. A complete application will include all of the following documents:
- a cover letter,
- curriculum vitae,
- a teaching statement: a document with a narrative describing your teaching philosophy and experience,
- a QM Experience Statement: a document with a narrative detailing your experience with quantitative methods,
- a Diversity Statement: a document describing how your work would contribute to QMSSs, the College of LSAs and University of Michigan's strategic commitment to diversity, equity and inclusion, and specifically to inclusive teaching practices and environments (https://sites.lsa.umich.edu/inclusive-teaching/),
- evidence of teaching excellence (student evaluations of teaching - scores and student comments),
- Three (3) letters of recommendation will also be required and must be submitted within 10 days of the application.
Job Summary
The Quantitative Methods in the Social Sciences in the College of Literature, Science, and the Arts at the University of Michigan seeks applicants for a full time new Lecturer III position with an anticipated start date of January 1, 2025. This is a non-tenure track position, with a University Year appointment period (i.e., runs September 1 through May 31 each year).
A typical full-time (100% effort) load for a Lecturer III in the College of Literature, Science, and the Arts is three (3) courses per semester, or the equivalent in administrative and/or service duties.
The initial appointment period will be one (1) to four (4) years (depending on qualifications), and the appointment may be renewed (based on programmatic need, funding, and performance). The appointment is subject to final approval by the college.
Mission Statement
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future
Responsibilities*
The lecturer will teach six course equivalents per year, with up to 33% of their course equivalents each term assigned to individualized/small group instruction and advising for students pursuing the minor in QMSS and co-curricular program development.
Initially, teaching will include existing courses developed by and/or in consultation with the Director of Quantitative Methods in the Social Sciences, particularly QMSS 301 - Quantitative Social Science Analysis and Big Data and QMSS 451 - Senior Capstone: Social Sciences Study Management. Other instructional responsibilities include overseeing course Graduate Student Instructor(s), holding office hours for students; individual and small group tutoring and project assistance, course planning and grading; and development of labs and online instructional tools and resources related to quantitative social science research and analysis. For instructional assignments including the senior capstone project course, the lecturer will also work along with program staff to identify, recruit and build relationships with external organizations partnering with the program in the capstone course.
The lecturers will serve as a departmental advisor for undergraduate students minoring in QMSS; assisting them with course planning, progress checks, transfer credit evaluation, study abroad credit exceptions and other petitions, career/graduate school counseling, misconduct issues, and senior audits. They will work with the QMSS Director and Steering Committee to identify needs for the program and make recommendations for curricular/program innovation.
The lecturer will also work with the staff in QMSS to plan program-wide and public events (guest speakers, alumni panels, workshops, etc.) geared towards undergraduate students minoring in and interested in QMSS. Additionally, they will collaborate with the LSA Opportunity Hub in helping students connect with relevant internship opportunities. This may involve bringing guest speakers to campus (who might also speak in classes, if appropriate), alumni panels, etc.
Required Qualifications*
- M.A. in a social science discipline with a demonstrated focus on quantitative methods, with a Ph.D. strongly preferred. Candidate must meet all degree requirements prior to the start date of the position.
- Experience teaching courses using quantitative methods and analysis, with proficiency in big data analysis and tools strongly preferred.
- Previous experience in project management and/or data consulting is strongly preferred.
- Proficient experience in R, Python, Excel, and Tableau.
- Successful candidates must have cutting edge and contemporary knowledge and experience in social science-oriented, big data-based research and/or teaching, with experience teaching undergraduate students strongly preferred.
Preference will be given to candidates who are social scientists with proficiency in all of the following: web scraping, working with big data, and data visualization.
Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.
Union Affiliation
This position is covered under the collective bargaining agreement between the U-M and the Lecturers Employee Organization, AFL-CIO, which contains and settles all matters with respect to wages, benefits, hours and other terms and conditions of employment.
Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
Contact Information
Questions about applying for this position can be emailed to: [email protected]
Application Deadline
Anticipated application deadline is October 2, 2024 and we anticipate we will schedule interviews in October. The offer to the final candidate is anticipated to be made before December 1, 2024
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.