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The Department of Industrial Engineering and Management Sciences (IEMS) at Northwestern University invites applications for a full-time, tenure-track faculty position at the level of assistant professor. This position is focused on candidates specializing in optimization with applications in various fields such as machine learning and data science, computational social science, healthcare, or logistics and operations. The ideal candidate should possess an earned PhD or be nearing completion of their doctoral studies, demonstrating significant research potential in a related area. A strong commitment to conducting rigorous and relevant research is essential for this role. The successful hire will have the opportunity to engage in interdisciplinary collaboration through various broad research initiatives and centers, including the Optimization and Statistical Learning, Center for Engineering and Health, Center for Deep Learning in IEMS, Center for Engineering Sustainability and Resilience, Institute for Data, Econometrics, Algorithms, and Learning, Institute on Complex Systems, and the Transportation Center within the McCormick School of Engineering. IEMS offers a comprehensive educational experience, including an undergraduate degree, a minor in machine learning and data science, a PhD program, and master's degrees in machine learning and data science as well as engineering management. Both the undergraduate and doctoral programs are consistently ranked among the top ten by US News & World Report. Candidates are required to submit their applications electronically, including a cover letter, curriculum vitae, research statement, teaching statement, diversity statement, and one research paper. In the cover letter, applicants should articulate their perspectives on the role of optimization and data science in both research and teaching within an IEMS department. Additionally, candidates will need to provide contact information for three references during the application process. To ensure full consideration, all application materials should be submitted by November 15, 2024, with a deadline of October 7, 2024, for first-round interview consideration.
