I have a remote work project that requires two or more part time student assistants. The key skill sets are using .graphml exports of Twitter data to help build a prototype tool for tracking the evolution of networks over time, and using a trust model to score accounts in the network based on their historical footprint. The hourly wage is negotiable. Job 1: If you are a network science student interested in the application of Kineviz GraphXR or similar tools I would like to discuss how you might help us transition from static pictures to dynamic historical mapping tools with a lower barrier to entry for new users. Job 2: If you have advanced python programming skills, the second opportunity involves learning to operate Trust Defender: https://github.com/texifter/trust-defender. This is a complex collection of open source scripts combining an n-gram Bayes classifier model with a neural network model which is used to classify Twitter users as potential good or bad actors. Ideally, the two positions will together help shape a new historical and interactive visualization where we can filter for a variety of trust score ranges in a dynamic network that allows real time drilling in and out of hubs and nodes. Please send me a CV, two references, and a short cover letter if you are interested. Assuming Twitter survives (there is some debate about this) we are going to need many new tools, teams, and methods to understand how U.S. election interference will operate in the run-up to 2024. -- Dr. Stuart W. Shulman Founder and CEO, Texifter Editor Emeritus, *Journal of Information Technology & Politics*