The Center for Language Science (CLS) is offering a new Ph.D. training opportunity for graduate students in the following programs:
The goal of the LinDiv graduate training program is to educate a new generation of experts in human-technology interaction who can bridge the gap between human linguistic diversity and technological linguistic illiteracy. The first LinDiv cohort began in Fall 2022, and current first-year and second-year graduate students in the above-listed programs are eligible to apply. NSF funding is limited to students holding U.S. citizenship or residency; a limited number of internally-funded fellowships are available for international students.
LinDiv provides a two-year training to students, including a one-year fellowship which includes tuition and stipend. LinDiv students cap their course work with a summer internship—also covered by the fellowship—with academic or private sector extramural partners to support careers bridging linguistics and technology. The two-year program culminates in a new graduate certificate ‘Linguistic Diversity and Technology.’ LinDiv training can be completed without significant delay to the student’s primary degree program and is compatible with the dual-title Ph.D. in Language Science.
LinDiv will train students in the skills and knowledge to successfully function in transdisciplinary teams, equip them with professional development skills to function effectively in a modern and inclusive workforce, and prepare them for a wide range of career paths in the US and abroad. LinDiv trainees will advance and empower diversity, equity, inclusion, and accessibility.
Program Timeline
Year | Coursework |
|---|---|
Year 1 | Fall: Basic Cross-Disciplinary Course (3 credits) |
Spring: Professional Development and Language Technology | |
Year-long: “Linguistics Meets Technology” colloquia | |
Year 2 | Fall: Advanced Cross-Disciplinary Course (3 credits) |
Spring: Transdisciplinary Team Research Project (Final Project) | |
Year-long: “Linguistics Meets Technology” colloquia | |
Year 3 | Cross-cohort Mentoring and Teaching |
Year-long: “Linguistics Meets Technology” colloquia |
Example Coursework
Basic Cross-Disciplinary Courses
For Language Science Students
- CSE 582: Natural Language Processing
- IST 597: Foundations of Deep Learning
- LDT 566: Using Technology to Expand Learning Processes
- LDT 577: Computer-Supported Collaborative Learning
- STAT 557: Data Mining
- IST 597: Principles of Machine Learning
- DS/CMPSC 442: Artificial Intelligence (Passonneau section)
- IST 597: Data Science for Researchers and Scholars
- IST 597: Engineering of Human-Centered AI Systems (Syed Billah)
For Non-Language Science Students
- LING 597: Linguistics and Language Science
Advanced Cross-Disciplinary Courses
For Language Science Students
- CSE 582: Natural Language Processing
- IST 597: Foundations of Deep Learning
- LDT 566: Using Technology to Expand Learning Processes
- LDT 577: Computer-Supported Collaborative Learning
- STAT 557: Data Mining I
- STAT 558: Data Mining II
- IST 597: Principles of Machine Learning
- CSE 584: Machine Learning: Tools and Algorithms
- DAAN 572: Reinforcement Learning
- DAAN 881: Data Driven Decision Making
- IST 521: Human-Computer Interaction: The User and Technology
- IST 520: Foundations in Human Centered Design
For Non-Language Science Students
- LING 502: Syntax II
- LING 504/SPAN 597: Advanced Topics in Phonological Analysis and Theory
- LING 519: Current Statistical Practice in Language Science
- LING 520: Seminar in Psycholinguistics
- DAAN 881: Data Driven Decision Making
- IST 521: Human-Computer Interaction: The User and Technology
- IST 520: Foundations in Human Centered Design
Final Project
Students form into transdisciplinary teams (3-4 students) to address a tractable goal and produce a clear product (e.g., a design project, pilot application, or research study) focused on integrating language science and human-technology interaction, in the context of linguistic diversity. This will be done by taking LING 597: Transdisciplinary Team Research Project. Some example projects include:
- Speech technology and smart voice assistants: Improve accessibility and usefulness for linguistically diverse language users
- Education: Human-technology interaction and inclusion of linguistically diverse students
- Life-long Language Learning technology: Grow the use of technology for language acquisition later in life