job description
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PhD thesis on intelligent interfaces: how generative AI reshapes knowledge, media and interpretation
Project Description
Artificial intelligence modeling (LLM) and other generative AI systems are integrated into everyday practice. Society is transitioning from an information retrieval paradigm, where search engines provide specific sources relevant to a particular query, to an interrogation and interpretation paradigm, where knowledge is embedded in AI models through extensive, often opaque, training processes and configurations. Artificial intelligence is also increasingly integrated into agent systems-designed for specific contexts, goals, and levels of autonomy-reconfiguring the way knowledge is generated, validated, and manipulated in domains such as journalism, research, and education. This shift raises critical questions about authority, transparency, and the evolving role of human expertise in AI-mediated workflows.
To critically assess this shift and learn from it, our project takes a two-pronged approach: first, we examine how research methods are embedded in AI tools, adopting a digital methods lens to explore their affordances and limitations. Second, we analyze how AI-driven software changes interfaces, affecting the way users access and interact with knowledge. Both approaches aim to understand how knowledge is constructed, accessed and used in digital research and everyday digital interactions.
What you will be working on
As a PhD on the project, you will be working on your own research agenda, which intersects with that of the Principal Investigator and falls into one of the following broad categories:
Epistemological shifts in generative AI – how does GenAI reshape knowledge validation, credibility and factuality processes? How do these patterns affect established knowledge gatekeeping institutions, and how do different models and modalities of GenAI shape the contexts in which it is used?
Workflow Transformation with Generative AI – How does GenAI reshape professional routines and decision-making in knowledge-intensive fields? How do AI-powered agent systems designed for specific contexts, capabilities, and goals redefine collaboration and expertise? How do they integrate and redefine existing software interfaces?
offer requirements
Your Tasks and Responsibilities
Submit your PhD thesis within the term of your appointment;
Participate in project research team meetings to develop shared databases;
Publishing a peer-reviewed, sole-authored article;
Presentation of interim research results at seminars and conferences;
Organizing knowledge dissemination activities;
Participating in doctoral training programs in the School of Research and the School of Humanities.
(Teaching of BSc courses (up to 0.2 working days per year) in the second and third (joint) years of the appointment.
What we ask of you
Candidates need to have the following qualifications:
Have completed a Master’s degree in Media and Communication Studies, Critical Artificial Intelligence, and Science and Technology Studies. If you have not yet completed your Master’s degree, you may apply but must provide a signed letter from your supervisor stating that you will graduate by September 1, 2025
Excellent research skills, as demonstrated by an excellent Master’s thesis, and the ability to publish in high-ranking journals and/or reputable publishers;
A strong collaborative attitude and willingness to engage in collaborative research;
Enthusiasm for disseminating academic research to non-academic audiences;
Good command of the English language
We are looking for a PhD candidate who can both critically investigate generative AI and explore its practical applications. The ideal candidate is neither solely focused on critiquing AI from a distance, nor on applying AI unreflectively without questioning its implications. Instead, we seek people who combine critical analysis with practical exploration – people who can both question the epistemological, social and technological dimensions of AI and experiment with its affordances in digital research methods and interface studies. Please note that you will not be admitted to the Ph.D. program at the University of Virginia if you already hold a Ph.D. or are pursuing a similar degree elsewhere.
Candidates should be adept at interdisciplinary work that bridges the gap between media and communication studies, critical artificial intelligence, and science and technology studies. Candidates should be analytical and open-minded, willing to explore the strengths and limitations of AI in knowledge production, dissemination, and professional workflows. Strong expository writing skills are essential, both to effectively command large-scale language models and to produce clear, rigorous scholarship. Experience with digital methods, such as data scraping and visualization, as well as a working knowledge of the underlying models (understanding their training processes and/or cues) is desirable. While not essential, proficiency in the Python programming language for numerical analysis would be an asset.
offer benefits/salary
We offer you
Ph.D. students are eligible for a tuition waiver;
D. students are entitled to free admission to courses offered by the Graduate School of Humanities and the National Research School of the Netherlands;
Excellent opportunities for further professional development and education;
An exciting academic and international working environment in the center of Amsterdam;
A welcoming and professional academic team.