The School of Information at UC Berkeley welcomes applications for two fulltime, nontenuretrack positions at the Assistant Adjunct Professor level, with an expected start date of July 1, 2019 in the area of Research Design, Ethics, and Data Science. These faculty members will teach in, help build, and be an integral part of the Master of Information and Data Science program (datascience.berkeley.edu), and will conduct research at the intersection of research design, ethics, and data science. Salary is commensurate with experience.
The position will include teaching in our online Master's program in Information and Data Science, service related to development, evaluation, and delivery of the Data Science program and courses, research collaboration, 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 these positions is on teaching and service to the Data Science program.
The minimum qualification required to be considered an applicant is a PhD (or equivalent international degree), or enrolled in a PhD (or equivalent international degree) granting program at the time of application. A PhD or international equivalent degree is required by the start date of the job.
Preferred qualifications (by start date)include a PhD in a relevant social science or interdisciplinary field such as Information, Information Science, Economics, Political Science, or Sociology. Preferred qualifications also include a demonstrated record of relevant research in designing and executing innovative experiments with data, demonstrated teaching in online synchronous classroom environments, as well as online course development (formation of educational goals, design of curriculum and learning activities). A successful candidate will possess appropriate technical expertise and relevant research, and be committed to working in a multidisciplinary setting. Relevant professional or industry experience in a data science role 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.
Candidates should demonstrate an active, productive research agenda related to research design and the ethical issues of data science. Ideally, candidates' research should focus on social science or data science domains, using quantitative and/or computational methods and approaches.
Applications must include:
Short statement of teaching experience
Short statement of research interests
Statement of contributions to diversity addressing past and/or potential contributions to diversity through research, teaching, and/or service
Course evaluations from any prior classes taught as instructor, co-instructor, or teaching assistant
Research and teaching link to a website demonstrating applicant's research and teaching expertise. (In case the applicant does not have a link to a website demonstrating research and teaching expertise, they can upload their materials here.)
Applicants must provide names and contact information for three letters of reference. Letters of reference will only be solicited for finalists. All letters will be treated as confidential per UC 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 http://apo.berkeley.edu/evalltr.html prior to submitting letters.
Criteria for evaluation will include: academic performance and publication record; a record of teaching, the ability to be selfdirected with broadlydefined 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.
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 startups as well as government and nonprofit organizations. Their jobs typically involve information design and architecture, usercentered design, document engineering, project management, consulting, webbased 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.
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: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct.
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The University of California was chartered in 1868 and its flagship campus - envisioned as a "City of Learning" - was established at Berkeley, on San Francisco Bay. Today the world's premier public university and a wellspring of innovation, UC Berkeley occupies a 1,232 acre campus with a sylvan 178-acre central core. From this home its academic community makes key contributions to the economic and social well-being of the Bay Area, California, and the nation.