Tamus

Tamus

Emerging Research Tools and Intelligence Librarian

College Station, TX · Contract

Sponsorship not specified$12k-$15kDetected 6 days ago
Data ScienceData VisualizationNLPComputer VisionLLMsResearchLeadershipCommunicationMentoring

About the role

  • From uncovering hidden strengths and connecting scholars to fostering collaborations and funding opportunities, this role will help position Texas A&M University for national prominence.
  • This role will transform complex data into actionable strategies and compelling impact narratives, driving smarter decisions and creating pathways for recognition and success.
  • The selected candidate will be expected to work on campus at our College Station, TX location.

Responsibilities

  • Design and pilot research support services based on trends and research needs.
  • Lead the assessment, adoption, and integration of emerging tools (e.g., generative AI, visualization platforms).
  • Partner with librarians and other units to embed tools into existing services.
  • Deliver one-on-one consultations on AI tools, impact narratives, or research planning.
  • Create and deliver workshops on emerging tools and research analytics.
  • Develop research support content for the library webpage and documentation.
  • Participate in conferences and monitor developments and best practices to enhance research support.

Requirements

  • Knowledge of academic library functions.
  • Knowledge or familiarity with AI-enhanced tools or emerging technologies such as generative AI, NLP tools, and research discovery platforms.
  • Excellent interpersonal and communication skills with the ability to communicate complex information clearly to varied audiences.
  • Familiarity with research analytics platforms (e.g., InCites, SciVal, Altmetric Explorer, Dimensions) and scholarly profile systems.
  • experience with emerging research tools and funding analysis, including matching researchers with grants or industry partners.
  • Knowledge of researcher development programs or national faculty award nomination processes.
  • Some coding or software development expertise.
  • Ability to navigate ambiguity and adapt rapidly evolving technologies and research trends.
  • Master's degree in Library Science, Computer Science, Data Science, Information Science, Research Analytics, or an equivalent combination of education and experience.
  • A well-qualified candidate may also possess:
  • Deep understanding of the research lifecycle and scholarly communication.
  • Demonstrated history of customer service.
  • Strong background in information management.
  • Understanding of bibliometrics and altmetrics for assessing research impact.
  • Ability to think strategically and innovatively to develop new services aligned with institutional priorities.

Skills

  • Glimpse of the Job
  • This is an in-person opportunity.
  • Guide use of AI and analytics tools to examine research profiles, project metadata, and impact metrics.
  • Identify gaps, emerging research directions, and strategic areas for growth.
  • Align internal strengths with funding opportunities, awards, and collaborations
  • Create visualizations, dashboards, and narratives showcasing research impacts.
  • Support researcher onboarding, mentorship matching, or award nominations.
  • Contribute to Library planning, committees, and task forces.
  • Participate in campus, regional, and national professional organizations.

Compensation

  • Compensation will be commensurate based on the selected candidate's education and experience.
  • Salary amounts will be discussed during the initial interview.
  • 12-15 days of annual paid holidays

Benefits

  • Health, dental, vision, life and long-term disability insurance with Texas A&M contributing to employee health and basic life premiums
  • Up to eight hours of paid sick leave and at least eight hours of paid vacation each month
  • Automatic enrollment in the Teacher Retirement System of Texas

This listing is sourced directly from Tamus's careers page and normalized into a canonical job model.