Scientometric analysis based on scholarly literature provides evidence-based support for describing trends and providing recommendations on science publication practices. For this project, we will apply scientometric techniques to address the real-world research questions: the impact of scientific publications on career trajectories, emerging trends in chemical and biomedical fields and the required information literacy skills associated with those trends. The project should culminate in a comprehensive report or presentation that showcases the student's contribution and its potential implications.

Students will also need to complete this library specific application.

Required Qualifications:

• U-M PhD student or Master’s degree student in good standing.

• Conversant in Python and use of Jupyter Notebook;

• Previous experience with pandas, seaborn, numpy, matplotlib, bokeh;

• Experience with API requests.

Position-Specific Desired Qualifications: 

• Ability to learn quickly, and to work independently;

• Attention to detail;

• Ability to meet deadlines; Good work ethics.

Expectations:

• Adhere to agreed-upon schedule and project deadlines, communicating any challenges or barriers to the mentors.

• Periodically attend Engagement Fellow training sessions and cohort meetings. 

• Publically share the project process and results with the library community near the end of the academic year.