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New Media Lab

THE NEW MEDIA LAB (NML) assists City University of New York (CUNY) Graduate Center faculty and doctoral students from a variety of academic disciplines to create multimedia projects based on their own scholarly research. Our goal is to integrate new media into traditional academic practice, challenging scholars to develop fresh questions in their respective fields using the tools of new technology. The NML is committed to a vision of new technology based on open access to ideas, tools, and resources.

With ongoing support from CUNY, the New Media Lab has become a dynamic environment in which projects funded by the National Endowment for the Humanities, the Rockefeller Foundation, the Old York Library Foundation, and other private and public sources demonstrate new approaches and methods of merging digital media, scholarship, and learning.

Located in room 7388.01 at the CUNY Graduate Center and run under the auspices of the Center for Media and Learning / American Social History Project, NML researchers:

work across academic disciplines to produce scholarly digital media projects;

analyze Internet usage in the educational, social, and commercial sectors;

construct 3-D environments that explore ways of visualizing the arts, humanities, and sciences

digitally archive and analyze a wide range of data
participate in public programs that address the critical intersection of knowledge and technology

Admins:

Job Opportunity: Research Assitant

  • Posted by Lisa Marie Rhody on October 13, 2017 at 3:05 am

    Hi all,

    Please help me get the word out. I am trying to find a research assistant to help with the next stage of my ongoing project. Thanks for sharing this job description widely!

    Best,
    Lisa

    ~~~~~~~~~~~~~~~~~~

    Job Title: Research Assistant

    Number of hours: 3-5 hours / week over 30 weeks

    Wages:  $44 / hour (Total: $3,500)

    Position description

    My project — Revising Ekphrasis — is a digital humanities experiment that involves topic modeling a corpus of 4,200 poems in English. I am looking for a research assistant who is interested in topic modeling and/or text analysis and poetry to assist me in updating my existing dataset for a new phase of my research. The next phase of the project involves translating scripts currently written in Scala (a computer language) and translating them into Python. Next,  we will collect additional data, clean it, and add it to the existing dataset, which we will use to create topic models with MALLET. The Research Assistant will update the code to collect, clean, prepare, and organize a poetic corpus of up to 8,000 poems, as well as help with duplicate checking, assigning metadata, and creating a replicable workflow for subsequent scholars to replicate our work. We will then take the data generated by topic modeling and experiment with a variety of visualization techniques to explore our results. Research assistants may have the opportunity to co-author publications based on this work.

    Key duties and responsibilities:

    • Help scrape and clean new dataset;
    • Translate Scala scripts to Python;
    • Document steps in the workflow accurately using git and GitHub;
    • Assist with running Topic Models;
    • Experiment with new modes of data visualization using D3.js;
    • Bi-weekly meetings and regular email correspondence.

    Qualifications:

    • Reading knowledge of Scala, or the ability to learn it quickly;
    • Advanced experience with Python, D3.js, and webscraping;
    • Some javascript experience;
    • Familiarity with MALLET;
    • Experience with network analysis visualization tools;
    • Strong communication skills;
    • Ability to work independently to meet deadlines;
    • Minimum requirement: at least one year of coursework at the graduate level.

    To apply, please send a letter of interest in the project, including your experience using Scala, Python, and javascript, and your experience with topic modeling and a current CV to [email protected] with the subject heading: RA Application. Applications will be reviewed on a first-come, first-served basis until the position is filled.

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