Fully funded PhD on Agent-based modelling for reconstructing the history of culture & language at Utrecht University

Comses; Utrecht; Hybrid; EUR 26,000 - 36,000; Full time

Benefits offered by this job

Fully funded PhD

Job summary

Utrecht University invites applications for a fully funded PhD position in agent-based modelling to reconstruct the history of culture and language in South America. The project blends geosciences, linguistics and data science within a multidisciplinary team.

The PhD candidate will analyse datasets spanning 20,000 years, develop a spatial ABM, and quantify the roles of biophysical and sociocultural factors shaping language diversity, under supervision from geographers and linguists.

Qualifications

• Master's degree in geoinformatics, computer science, data science, geography, linguistics, or related field with computational/data science component.
• Strong programming and data analysis skills.
• Fluency in English and ability to work in multilingual, interdisciplinary teams.

Responsibilities

• Develop an agent-based model to study language evolution.
• Analyse sociocultural and biophysical factors using large datasets.
• Collaborate with Utrecht University and Leiden University teams.
• Contribute to teaching and support PhD candidates (≈20% of time).

Skills

Python programming

Spatial data handling

English proficiency

Independent work

Interdisciplinary teamwork

Education

Master's degree in geoinformatics / CS / data science / geography / linguistics

Job description

Fully funded PhD on Agent-based modelling for reconstructing the history of culture & language at Utrecht University

The aim of this project at Utrecht University (the Netherlands) is to understand and quantify the roles of sociocultural and biophysical factors in the evolution of linguistic diversity using an agent-based modelling approach. The spatial agent-based model should simulate how and where languages (agents) change, merge, and split over time. You will use linguistics theory in combination with large datasets of environmental, demographic, sociocultural and linguistic variables to define the model rules.

The project is a geoinformation and data science challenge and at the same time uses domain-specific knowledge from linguistics. In this project, you will:

• analyse data on biophysical and demographic variables across South America since 20,000 years ago;
• develop a spatial agent-based simulation model of language evolution;
• use this model to quantify the relative role of biophysical and sociocultural factors in shaping language diversity in South America.

You will work in a multi-disciplinary team consisting of modellers, data scientists, research software engineers, linguists, and geographers from the Faculty of Geosciences, Utrecht University. You will closely cooperate with a PhD candidate in linguistics at Leiden University. Both of you will work on the same case studies in South America.

To support academic and personal development, PhD candidates follow courses and assist in teaching at Bachelor’s and Master’s level. Together these activities amount to twenty percent of the contracted time.

Language is a unique proxy for culture. A language family arises as a result of the diversification over time of the speech variants of groups that once spoke one and the same language but followed differential historical trajectories. These socio-historical processes took place all over the world, but they have led to radically different patterns of linguistic diversity from one area to another. This fully-funded NWO Open Competition L project is a collaboration between Utrecht University faculty of Geosciences and Leiden Centre for Linguistics to understand the interplay between the biophysical environment and the social processes of diversification to explain the patterns of linguistic diversity we see today external link.

We look forward to your application if you have the following qualifications:

• MSc in geoinformatics, computer science, (spatial / geographic) data science, or alternatively in a thematic domain, such as geography, linguistics, ecology, social science, with a considerable component of computational science or data science;
• interest in the historical dynamics of culture and language;
• experience in handling spatial data;
• programming and modelling experience, preferably in Python;
• proficiency in English;
• strong communication skills;
• ability to work independently as part of an interdisciplinary research team.