Job Description

JOB DESCRIPTION:
A Post-doctoral Associate in Social Network Analysis position is available for up to 2 years to work within the NSF supported project: Measuring the dynamic impact of personal social networks on language learning outcomes (NSF-2341628) led by Dr. Eleonora Rossi in the Department of Linguistics, together with an interdisciplinary team of co-PIs experts in network science (Dr. Christopher McCarty), corpus linguistics (Dr. Stefanie Wulff), computational linguistics (Dr. Zoey Liu), and Spanish Linguistics (Dr. Diego Pascual y Cabo) beginning ideally August 18, 2025.

The project uses interdisciplinary methods from social network science, language modeling, and cognitive science. In this longitudinal project we will follow learners of Spanish who are enrolled in Spanish classes. Over the course of the study we will collect personal social network data, several language measures through written and oral tasks, and measures of cognitive aptitude. The goal of the project is to understand if and to what extent compositional and structural network measures predict language learning and language maintenance metrics in Spanish learners.

The successful applicant for this position will be key to coordinate and partake in collecting personal social network data in collaboration with a PhD candidate supported by the project. In addition, the successful applicant will be in charge of conducting the personal social network modeling for the collected data and will be involved in the preparation of subsequent manuscripts for publication and attend national and international conferences that may be fitting the project.

Candidates must have a PhD in any quantitative discipline in the social sciences with a specialization in network science including Linguistics, Sociology, Anthropology, Cognitive Science, and related disciplines by August 2025.

This position will be initially awarded for one year, and, contingent upon strong performance and conduct and availability of funds, may be renewed for up to one year.

UF is the state’s oldest, largest, and most comprehensive land grant university with an enrollment of over 50,000 students and was ranked 7th in the country among public universities (US News and World Report 2025 rankings), and 1st among public institutions in the Wall Street Journal 2023 survey. UF is located in Gainesville, a city of approximately 150,000 residents in North-Central Florida, 50 miles from the Gulf of Mexico, and 67 miles from the Atlantic Ocean, and within a 2-hour drive to large metropolitan areas (Orlando, Tampa, Jacksonville). The beautiful climate and extensive nearby parks and recreational areas afford year-round outdoor activities, including hiking, biking, and nature photography. UF’s large college sports programs, museums, and performing arts center support a range of activities and cultural events for residents to enjoy. Alachua County schools are highly rated and offer a variety of programs including magnet schools and an international baccalaureate program. Learn more about what Gainesville has to offer at Visit Gainesville.

EXPECTED SALARY:
The salary is competitive and commensurate with qualifications and experience, and the compensation includes a full benefits package. To learn more, visit, benefits.hr.ufl.edu.

MINIMUM REQUIREMENTS:
Successful applicants will have the following profile:

-Be experts in social network analysis and have completed a PhD in any quantitative discipline in the social sciences with a specialization in network science including Linguistics, Sociology, Anthropology, Cognitive Science, and related disciplines by August 2025.

-Candidates should have excellent skills in designing, conducting and analyzing Social Network data.

-Excellent data analysis skills in R, Python, and/or Matlab are required.

-Ability to work independently and collaboratively.

-Excellent communication and organizational skills.

PREFERRED QUALIFICATIONS:
Successful candidates should also have the following preferred qualifications:

-Have experience and/or interest in applying Social Network Metrics to language and cognitive outcomes.

-Have experience and/or interest to acquire expertise in machine learning applied to language modeling.