[Corpora-List] USC/ISI Summer Internships

Jonathan May jonmay at isi.edu
Tue Dec 18 23:37:18 CET 2018


We (Jonathan May and Violet (Nanyun) Peng) are looking for interested and qualified students (graduate and undergraduate) to spend the summer working with ongoing research projects at USC/ISI in Los Angeles, CA, USA on natural language processing, machine learning, statistical modeling, machine translation, automata, and other areas.

These are paid internships. They will be available for a three month period during the summer of 2019.

Good programming skills are required, but prior experience in natural language processing is not necessarily required. We will provide tutorials on relevant topics at the beginning of the summer.

Important dates

2019 Jan 25 Applications due 2019 Feb 22 (approx.) First acceptance notifications 2019 Jun 10 Internships begin

Project Areas of Interest

Neural Machine Translation.

Why does neural machine translation work as well as it does? We know we can transfer from high to low resource but we don't know why. When is Transformer better than seq2seq? How do we avoid reinventing the wheel with each new data scenario?

Tools for All Languages.

Today's automatic parsers, translators, and pronunciation dictionaries cover a tiny fraction of the world's languages. Can we use general knowledge of how language works to extend the reach of natural language tools?

Creative Language Generation.

In the not-too-distant future, stories, poems, songs, and advertisements will be written by machines and human-machine collaborations. We are starting down this path now (for example, see here and here), and there are many research avenues to pursue.

Commonsense Reasoning.

A simple story: Janice got into her car and sped off. Question: Did she press on the accelerator? An AI system needs to know a lot to answer simple questions like this. Can an AI system obtain such knowledge by reading text?

Multimodal Representations.

A picture is worth a thousand words. How many words is a song worth? Humans perceive multiple modalities and this perception is mutually reinforcing. Can a big "brain" that understands the close relationships between modalities improve modern NLP tasks?

Information Extraction.

There is abundant knowledge carried in the exponentially expanding corpora of natural language texts. Yet this knowledge is mostly inaccessible to computers and overwhelming for human experts to absorb. From a strong foundation, we want to build knowledge graphs to dramatically increase the accessibility of knowledge through search engines, interactive AI agents, and medical research tools.

For more information please visit https://www.isi.edu/projects/nlg/summer_internships

Or to apply right now, please follow the instructions below. Applications that do not conform will be rejected without review.

Submit your application no later than January 25, 2019, by email to nlsummer at isi.edu with the subject: "Application: <applicant name>". Your application should include:

* A CV or resume, as a PDF file. * A statement of purpose, as a PDF file. It should indicate what project areas you are interested in. * The name and email address of one or more people whom you have asked to write you a recommendation letter.

Recommenders should send letters no later than January 25, 2019, directly to nlsummer at isi.edu with subject: "Recommendation: <applicant name>". Letters should be in PDF or plain text format.



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