How to Apply:

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

Please submit 1 PDF FILE that contains your resume and a brief cover letter describing your relevant experience and interest in the project. In your cover letter, include links to examples of relevant work (e.g., a GitHub repository) to https://www.dropbox.com/request/IsSz7I7Kzx47HjY5lpJe

Application Deadline: 12/19

Job Summary:

We are seeking a motivated Student Programmer to assist with data collection, cleaning, and management tasks for an active research project focused on Knowledge Graphs (KGs) of scientific activity.

The goal of this project is to model the scientific ecosystem (including datasets, research papers, authors, institutions, and funding sources) as a large-scale knowledge graph to facilitate new kinds of data-driven analysis and discovery. You will be working directly with faculty and other student researchers.

The Team

• Prof. Libby Hemphill

• PhD student Ji Eun Kim

• Collaborator Dr. Sara Lafia at NORC

Responsibilities:

The programmer will primarily focus on tasks essential for building and maintaining the knowledge graph.

• API Integration & Data Collection: Develop and maintain Python scripts to interact with various APIs (e.g., scholarly databases, institutional repositories) to collect structured and semi-structured scientific metadata.

• Data Cleaning and Transformation: Implement data processing routines in Python to clean, normalize, and transform raw data into a format suitable for graph modeling.

• Graph Database Management: Load, update, and manage data within the Neo4j graph database. This includes writing and optimizing Cypher queries for data manipulation and ensuring data integrity.

• Documentation: Maintain clear and thorough documentation of data sources, collection scripts, and data schema.

Required Qualifications:

• Proficiency in Python (including experience with libraries for data manipulation like pandas) and Jupyter Notebook.

• Experience working with APIs for data retrieval (e.g., using requests library).

• Familiarity with or willingness to rapidly learn Neo4j and the Cypher query language.

• Experience with version control systems, especially Git.

• Solid understanding of data structures, data modeling concepts, and basic database principles.

• Reliable, detail-oriented, and able to work independently on assigned tasks.