Assistant Adjunct Professor, Experiments and Data Science

The School of Information at the University of California, Berkeley welcomes applications for a full‐time, non‐tenure‐track position at the Assistant Adjunct Professor level, with an expected start date of July 1, 2018, in the area of Experiments and Data Science. This faculty member will teach in, help build, and be an integral part of Master of Information and Data Science program (, and to conduct research at the intersection of experiments and data science.

The position will include teaching in our online master’s program in Information and Data Science, research collaboration, service related to development, evaluation, and delivery of the Data Science program and courses, and participation in the intellectual community at the School of Information and on the Berkeley campus. While research is an important aspect of this role, the focus of the responsibilities of this position is on teaching and service to the Data Science program.

Recruitment Period

Open December 5, 2017 to January 31, 2018.

First review: January 15, 2018. Apply by this date to ensure full consideration by the committee.


The minimum qualification to be considered as an applicant for the position is a doctoral degree or equivalent degree, or all degree requirements except the dissertation, in a relevant social science or interdisciplinary field such as Information, Information Science, Economics, Political Science, or Sociology, at the time of application. A successful candidate will possess appropriate technical expertise and research excellence, and be committed to working in a multidisciplinary setting. A Ph.D. or equivalent degree is required by the date of hire.

Preferred qualifications (by start date) include a demonstrated record of relevant research in designing and executing innovative experiments with data, demonstrated excellence in teaching in online synchronous classroom environments, as well as online course development (formation of educational goals, design of curriculum and learning activities). Relevant professional or industry experience is also desirable. The School is interested in candidates who will contribute to diversity and equal opportunity in higher education through their teaching, research, and service.

Additionally, the successful applicant will be expected to have excellent command of industry standard software and workflow as it relates to the implementation of experiments in data science. This should include expert level mastery in core data science languages (R and python), expertise with experimental modules within these languages, and version controlling awareness using git and GitHub.

Candidates should demonstrate an active, productive research agenda related to experiments, experimentation, and causal inference. Ideally, candidates’ research should focus on social science or data science domains, using quantitative and/or computational methods and approaches.

Criteria for evaluation will include: a superlative academic performance and publication record; the ability to be self‐directed with broadly‐defined limits on assignments; excellent communication skills, both oral and written; a demonstrated ability to interact efficiently with diverse people in a highly multidisciplinary environment; and some industry experience in a data science role.

About the School of Information

The School of Information is the most recently formed school on the Berkeley campus. We are a multidisciplinary professional school. Our faculty members come from diverse fields, including political science, sociology, economics, law, engineering, computer science, media arts and design, and information science. We share a commitment to building a new field of scholarship and practice that addresses the design of new genres of information, information systems, and media, information policy and ethics, and the relationships among information/ information systems and individuals, organizations, and society.

Our master’s graduates are employed in corporations and start‐ups as well as government and non‐ profit organizations. Their jobs typically involve information design and architecture, user‐centered design, document engineering, project management, consulting, web‐based information services, and information policy and science. Graduates of our PhD program have taken positions in places such as the Heinz School of Public Policy and Management at Carnegie Mellon, the Berkman Center for Internet and Society at Harvard, and Microsoft Research. We also offer undergraduate courses in fields such as new media and the history of information.

How to Apply

To apply, please submit all materials electronically to the following URL This position is open until filled.

Applications must include:

  • A cover letter
  • Curriculum Vitae
  • A short statement of teaching experience
  • A short statement of research interests
  • Course Evaluations from any prior classes taught as instructor, co‐instructor, or teaching assistant
  • Three selected publications
  • Statement of contributions to diversity: a statement addressing past and/or potential contributions to equity and inclusion through research, teaching, and/or service
  • A link to a website demonstrating applicant’s research and teaching expertise

Three letters of recommendation will be required. All letters will be treated as confidential per University of California policy and California State law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letters.

Questions may be sent to


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, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see:

Last updated:

December 6, 2017