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Tenure-Track/Tenured Faculty Position in Library and Information Science


Rutgers University, School of Communication and Information

Application Deadline: October 15, 2023.


The Library and Information Science (LIS) Department in the School of Communication and Information (SC&I) at Rutgers University, New Brunswick, invites applications for a Data Science tenure track appointment as part of a larger interdisciplinary Fair and Responsible Data Science (FRDS) cluster hire at Rutgers supported by the Rutgers Presidential Diversity Hiring Initiative.


Information about the FRDS initiative may be found here. Other Rutgers units hiring in FRDS include School of Arts and Sciences (Computer Science and Statistics) and Engineering.


Across the School of Communication and Information’s 75 full time equivalent faculty, about 20 focus on scholarship related to FRDS. The LIS department is a founding member of the iSchools Consortium and has a research and learning culture that is inclusive, diverse, and cohesive, international in scope and local in impact. The LIS tenure-track/tenured appointment in Fair and Responsible Data Science may be at the Assistant Professor, Associate Professor or Full Professor levels.


Hiring Criteria:

  • Ideal candidates would be world-class data science researchers who advance the field of human-centric data science with novel technical and social innovations and/or apply data science to novel contexts in fields related to communication, information, and media.

  • Such candidates would have a track record of scholarship and technical expertise in fields such as responsible AI, algorithmic fairness, information visualization, network science, and/or designing novel data-driven frameworks in contexts such as social computing, wearable computing, health computing, misinformation, privacy, etc. Faculty hired in Data Science will be well-positioned to lead externally funded research projects in such areas.

  • Ideal candidates would be methodologically rigorous and adept at bringing core data science ideas to fruition in interdisciplinary settings. Candidates who transcend traditional research topics, complement our faculty’s strengths, and can teach across our undergraduate and graduate programs are highly sought for application.

  • Candidates should speak to their record of engagement, accomplishment, and / or potential for academic, professional, and/or institutional work undertaken to advance diversity, equity, and inclusion either in their cover letter or in a separate written diversity statement. Through this initiative, we will strongly emphasize hiring faculty who can help advance diversity, equity, and inclusion at Rutgers and especially in enhancing DEI in STEM. The University Statement on Diversity can be found here.

We look forward to welcoming a new colleague who will contribute to our thriving undergraduate and master’s level programs in LIS and our highly-regarded interdisciplinary school-wide Ph.D. program, and will be expected to contribute as relevant to wider Data Science cluster initiatives in research and education programs at Rutgers.


Minimum Education & Experience

A Ph.D. or equivalent doctoral degree in a relevant field is expected as of June 2024 for a September start date. Applicants should have a demonstrated record or strong likelihood of top-tier peer-reviewed publication and evidence of or preparation for effective teaching. Applicants at the rank of Associate Professor or above should provide evidence of leadership in research, instruction, and service; a record of external funding is a plus. Responsibilities of tenure-track and tenured faculty members include undergraduate and graduate teaching assignments, an active program of research in the candidate’s area of scholarly expertise, and service contributions in accordance with the university policy for tenure‐track and tenured appointments.


Review of applications will begin October 15, 2023, and will continue until the position is filled. Candidates are required to submit a letter of application; a brief statement that demonstrates how your research/teaching advances DEI in STEM; CV; two sample publications and the names of three references. Inquiries can be made to Prof. Rebecca Reynolds, Chair, Department of Library and Information Science, Rutgers University, 4 Huntington St., New Brunswick, NJ.


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