Open date: April 12th, 2019
Last review date: Tuesday, Jan 21, 2020 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
Final date: Tuesday, Apr 7, 2020 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
The School of Information at the University of California, Berkeley seeks applications for multiple Postdoctoral Scholars, in the area of Data Science, at 100% time, to help conduct research, teach in, build, and be an integral part of our web-based Master of Information and Data Science program (datascience.berkeley.edu).
The number of positions varies from semester to semester, depending on the needs of the School. Positions typically start in January, May, and August, and appointments may be renewed based on need, funding, and performance.
The position will include teaching sections in our online Master’s program, research collaboration, and participating in the intellectual community at the School and on the Berkeley campus. Research responsibilities include pursuing a self-directed research agenda, presenting current research to the community, and participating in research exchange events. Teaching responsibilities include lecturing, holding office hours, grading, assigning grades, advising students, and preparing course materials. Postdocs are expected to teach up to 8 small sections per year as a Lecturer.
About The I School
UC Berkeley’s newest school, the School of Information (I School), was created in 1994 to address one of society’s most compelling challenges: the need to organize and make sense of the abundance of information that we can now collect, store, and share without regard for cost or distance. The way we organize, represent, govern, and make sense of this information will shape our ability to achieve public as well as private goals.
The I School educates professionals and scholars to understand the problems and possibilities of information, to develop models of information practice, and to design useful and usable information applications, services, and solutions. This requires insights from diverse fields. Our faculty includes scholars and professionals with deep expertise in information and computer science, social sciences, management, law, design, and policy, as well as related fields.
We offer professional master’s degrees and an academic doctoral degree. Our on-campus master’s program (MIMS) trains students for careers as information professionals and emphasizes small classes and project-based learning. Our MICS program prepares cybersecurity leaders with the technical skills and contextual knowledge necessary to develop solutions for complex cybersecurity challenges. Our web-based master’s program (MIDS) is the first and only degree available completely online to train data science professionals. Our Ph.D. program equips scholars to contribute to knowledge and to the policies that influence the organization, use, and sharing of information.
Our graduates work at an impressive variety of well-known Bay Area tech companies, nonprofits, and public sector entities. Many of our graduates take advantage of the opportunity to get in on the ground floor to create or work for start-ups.
Basic qualifications (by time of application):
PhD (or equivalent international degree) or enrolled in a PhD (or equivalent international degree) program.
Additional Qualifications (by start date):
A PhD (or equivalent international degree is required).
Successful candidates will have earned a doctoral degree in a field such as Data Science, Information, Information Science, Statistics, Computer Science, Engineering, Political Science, Sociology, Law, or Economics. The Data Science postdoc will have teaching and research experience in at least one of the following core areas:
• Research design and data analysis
• Applied statistics
• Data engineering, storage, retrieval
• Visualizing and communicating data
• Applied machine learning
• Privacy, security, and ethics of data
• Experiments and causal inference
• Very large scale data mining and analysis
• Applied regression and time series analysis
• Deep learning
• Social network analysis
• Natural language processing
A record of authored publications or articles in preparation.
Preferred qualifications include the ability to be self-directed with broadly-defined limits on assignments; excellent communication skills, both oral and written; and a demonstrated ability to interact effectively with diverse people in a highly multidisciplinary environment.
Starting salaries are typically in the range of $60,000 to $65,000 per year and commensurate with qualifications and experience.
The total duration of an individual's postdoctoral service may not exceed five years, including postdoctoral service at other institutions.
To apply, please go to the following link: https://aprecruit.berkeley.edu/JPF02162
This pool will remain open until April 7, 2020 to accommodate course needs and new applicants. Appointments are made for three starts per year: fall, spring, and summer. If you wish to remain in the pool after April 7, 2020 you will need to reapply.
All letters of reference will be treated as confidential per University of California policy and California State law. Please arrange for letters of recommendation to be uploaded directly by recommenders. 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 their letters.
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
The School of Information is interested in candidates who will contribute to diversity and equal opportunity in higher education through their teaching or other related areas. We require that applicants submit a statement addressing past and/or potential contributions.
UC Berkeley has an excellent benefits package as well as a number of policies and programs to support employees as they balance work and family, if applicable.
Please direct questions to firstname.lastname@example.org.
Curriculum Vitae - Your most recently updated C.V.
Statement of Teaching Interests/Experience/Approach - Please indicate which MIDS class(es) you are qualified to teach.
Statement of Research Interests/Experience/Approach
Statement on Contributions to Advancing Diversity, Equity, and Inclusion - Statement on your contributions to diversity, equity, and inclusion, including information about your understanding of these topics, your record of activities to date, and your specific plans and goals for advancing equity and inclusion if hired at Berkeley (for additional information go to https://ofew.berkeley.edu/recruitment/contributions-diversity).
PDF Copy of Recent Publication or Manuscript in Preparation
PDF Copy of Recent Publication or Manuscript in Preparation (Optional)
Course Evaluations - We encourage you to send evaluations from any prior classes taught (as instructor, co-instructor, or teaching assistant)
- 3 letters of reference required