2024 - 2025 Assistant Professor of Technology, Operations and Statistics (Tech) - Full-time, Tenure-Track
New York University
Location: New York, NY
Internal Number: 130469
The Technology faculty in the Department of Technology, Operations and Statistics at the Stern School of Business, New York University, invites applications for a tenure-track position at the Assistant Professor level starting in the 2024-25 academic year. Candidates should hold a Ph.D. in Information Systems or a related discipline, or must successfully defend their doctoral dissertation prior to appointment, and must be qualified to contribute to the department's teaching at the undergraduate, MBA and Ph.D. levels. Technically strong candidates with expertise in machine learning who have the potential to contribute to teaching programming, data science, and business analytics are strongly preferred.
The Technology faculty is a multidisciplinary group of computer scientists, economists, behavioral scientists, and data scientists. It has a vibrant Ph.D. program with a history of successful placements at top schools. The group provides a supportive environment for nurturing independent inquiry early in one's career. Our faculty, students and scientists have won numerous awards for their research and scholarship over the last decade.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $140,000 - $230,000. This pay range represents base pay only (for 9 months) and excludes any additional items such as incentives, bonuses, clinical compensation, or other items. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as market and organizational considerations when extending an offer.
We are especially interested in candidates with strong interpersonal and collaborative abilities, potential to add to the innovative intellectual life of the group, and discipline-spanning interests that complement the research programs of our existing faculty in areas that include Artificial Intelligence, Business Analytics, Causal Inference, Computational Social Science, Data Science, Digital Marketing, Digital Strategy, Machine Learning, Network Science, Online Marketplaces, Organizations, Recommender Systems, Platforms, Tech Regulation, and Web3.
Applications must include an up-to-date curriculum vitae, personal statements describing research and teaching (if any) experience along with future plans for research and teaching, and three letters of recommendation. Research papers should be included if available.
Please send questions to firstname.lastname@example.org. To ensure full consideration, the deadline for submitting all application materials is Sunday, September 17, 2023. Please be responsive. However, applications will be accepted and evaluated until the position is filled. We expect to start interviewing candidates in late September..
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