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Tenure-Track or Tenured Faculty in Online Platform Design and Analysis


University of Michigan, School of Information

University of Michigan, School of Information

Application Deadline: November 30, 2023


Description

The University of Michigan’s School of Information (UMSI) seeks a tenure-track assistant, associate, or full professor in the field of online platform design and analysis. We seek candidates whose research combines insights from the behavioral sciences with market design thinking to focus on solving real-world problems. We welcome applications from scholars in the social or behavioral sciences, computer or information science, or statistics among others. Applicants whose work integrates behavioral design to study large-scale social phenomena, especially when combined with technology, will be particularly well-suited for this position. Competitive applicants will have a unique blend of quantitative skills in designing new institutions or platforms (“market design”), with expertise in identifying causal relationships in large-scale data sets from socio-technical domains (“analysis”). Information technology facilitates the design and evaluation of solutions to real-world social problems at scale and low cost. UMSI has a unique group of faculty members with quantitative and computational skills to take advantage of the unprecedented availability of data to gain new knowledge and to solve real-world social problems. Recent applications of randomized controlled trials to socio-technical domains have generated valuable insights into causal factors which address systemic racism present in online platforms, promote prosocial peer-to-peer lending to entrepreneurs in developing countries, encourage people to exercise more and physicians to change antibiotic prescribing behavior, facilitate job search and wage equity, contribute to open content, protect privacy, and optimize social and political marketing campaigns in a time of unprecedented mis- and information glut. We especially encourage applicants who work in the areas of adaptive experimental design, market design, privacy, evaluating bias on platforms, anti-racist online platform design, economic applications of machine learning, and ICT for development. We are open to the domain of study. Examples include (but are not limited to) economics of AI; economics of social networks; recommender and reputation system design; the future of work; race and racism in platform design or information aggregation; health and behavior change; digital advertising; ICT for development; user-generated content and other public goods problems; crowdsourcing; privacy; collective intelligence and other information aggregation problems.


The successful candidate should demonstrate potential for or experience with publication and research funding, for collaborative and interdisciplinary initiatives, and for working with students from diverse backgrounds.


Job Expectations and Responsibilities

Job duties include research, teaching, and service. Job responsibilities include but are not limited to:

  • Conducting scholarly research resulting in publications in peer reviewed journals, book chapters, edited books, books, and conference proceedings

  • Seeking outside funding to support their research program

  • Teaching in UMSI’s five academic programs

  • Mentoring students for independent studies, master’s projects and theses, and doctoral dissertations

  • Providing service to the school, University, and the broader academic community by way of committee work, journal editing, and other various opportunities

Each contributing member of the UMSI faculty is expected to have teaching effort equivalent to three semester-long courses per year.


About UMSI and UM

The mission of the School of Information is to create and share knowledge to help people use information -- with technology -- to build a better world. A successful candidate will be committed to, and will directly contribute to, our goal of being the best research and teaching institution for the understanding and design of information and its technologies in service of people and society.


The School is home to vibrant research and teaching programs, with 74 FTE professors, and over 1,803 students. We offer five degrees: a Ph.D., a Master of Science in Information, a Master of Health Informatics, a Bachelor of Science in Information, and an online Master of Applied Data Science.


Founded in 1817, the University of Michigan has a long and distinguished history as one of the first public universities in the nation. It is one of only two public institutions consistently ranked among the nation's top ten universities. The University has one of the largest health care complexes in the world and one of the best library systems in the United States. With more than $1.53 billion in research expenditures annually, the University has the second largest research expenditure among all universities in the nation. The University has an annual general fund budget of more than $2.3 billion and an endowment valued at more than $12.5 billion.


For more information about UMSI, please visit: www.si.umich.edu


Minimum Job Qualifications

  • Ph.D. in an area such as economics, social and decision sciences, computer science, information science, statistics, informatics, or a related field.

  • A strong commitment to connecting information, technology, and people.

  • A strong commitment to interdisciplinary research and cultural diversity.


Desired Qualifications

  • Demonstrated potential for high scholarly impact.

  • Demonstrated potential for successful teaching at the undergraduate and graduate levels.

How to Apply

All applicants for this tenure-track or tenured faculty position should submit a cover letter that highlights their qualifications and interest in UMSI, a vita, three representative papers, evidence of teaching excellence if available, a research statement, a teaching statement, a diversity statement. Applicants at the assistant professor level must submit three letters of recommendation; applicants at the associate and full professor level must submit the names of three recommenders.


All application materials must be submitted electronically to: http://apply.interfolio.com/133785


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