Run by the Data Science Institute and the Mansueto Institute, the Local Data Journalism Initiative establishes partnerships between news organizations and university data science teams using the highest caliber data science and artificial intelligence tools and methodologies.

What sets this effort apart from existing university data journalism programs is that, rather than attempting to train reporters to be data scientists in a few weeks, we connect them with university faculty and students who will conduct data science projects and provide analyses and visualizations needed to complete their stories. This empowers journalists to do what they do best: investigate leads; build relationships with sources; and tell powerful, impactful stories — knowing that the data and results they’re reporting have been rigorously analyzed and validated.

Fellows will receive compensation at a rate of $26 per hour over the eight weeks.

Eligibility

The program is intended for graduate students and advanced undergraduate students at the University of Chicago with a background in mathematics, computer science, and/or data science, as well as experience collaborating with and supporting peers, particularly those from groups underrepresented in STEM.

Candidates can have experience or interest in any of the following areas of research: Computer Systems and Architecture, Data Science and Machine Learning, Deep Learning, Hardware & Devices, High-Performance Computing, Human-Computer Interaction, Natural Language Processing, Networking, Security and Privacy, Arts & Culture, Biology & Medicine, Communications & Internet, Economics and Business, Energy, Environmental Sciences, Food and Agriculture, Human Rights, Public Policy, Physics and Astronomy.

Candidates should also have experience with any of the following data science tools: Web (HTML/Javascript), Java, Python, C/C++, Data Analysis, Jupyter Notebooks, Linux, Machine learning, GitHub, or Databases/SQL.

Deadline

Reviews will begin February 17th, 2025 and will continue until positions are filled

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