PhD on AI as a Social Agent to Support Group Learning Processes

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

The Department of Applied Physics and Science Education is a research-driven department housing high-quality educational programs all featuring strong connections between research and education. Our research is clustered in three focal areas: Fluids Bio and Soft Matter (FBSM); Plasmas and Beams (PB); and Nano Quantum and Photonics (NQP). Our shared ambition is to equip the next generation of engineers of the future with the knowledge and the skills they will need to impact science innovation and society from regional to global scales.

Introduction

Are you passionate about using AI to understand and support group learning processes in Challenge-Based Learning environments

Eindhoven University of Technology invites applications for a PhD position within the recently NRO-funded research project AI as a Social Agent to Support Group Learning Processes. This interdisciplinary project explores how AI specifically large language model (LLM)-based chatbots can act as adaptive social agents to support students collaborative learning in Challenge-Based Learning (CBL) environments.

The PhD position is part of a larger NRO-funded initiative that brings together experts from TU/e the University of Twente and Maastricht University. The project combines educational sciences artificial intelligence and innovation studies. Within this consortium a PhD student and a postdoctoral researcher will work closely together to address both the educational and technical challenges of using AI to enhance socially shared regulation of learning (SSRL).

This PhD project will focus on identifying socio-cognitive and socio-emotional triggers in student collaboration designing scaffolding strategies to address them and investigating students perceptions of AI as a learning partner during teamwork. The findings will directly inform the development of adaptive AI tools led by the postdoctoral researcher.

A central question that guides this PhD research is

How can an AI social agent be theoretically designed and effectively implemented in a CBL context to support collaborative tasks

Job Description

As a PhD student you will:

• Conduct literature reviews on metacognitive and emotional regulation in collaborative learning with emphasis on how regulation unfolds in both team interactions and humanAI collaboration.
• Identify and categorize socio-cognitive and socio-emotional triggers in CBL contexts to inform the design of responsive AI-based scaffolds.
• Design and evaluate scaffolding strategies in close collaboration with a postdoctoral researcher ensuring the AI social agent is co-developed and empirically grounded.
• Collect and analyze multimodal data (e.g. video audio interaction logs) from student group collaborations and interactions with the AI social agent.
• Conduct classroom studies to implement and evaluate AI-supported interventions.
• Disseminate findings through journal articles conferences workshops and practice-oriented outputs.

Job Requirements

We are looking for an enthusiastic candidate with:

• A Masters degree (or equivalent) in Educational Sciences Learning Sciences Educational Psychology or a closely related discipline.
• Strong interest in interdisciplinary research at the intersection of education and AI.
• Proven affinity with artificial intelligence in education (e.g. prior coursework research projects or collaborations). A track record in this area (e.g. thesis publications or practical applications) will be considered a strong plus.
• Experience with (or willingness to learn) mixed-method research including qualitative and quantitative approaches.
• Affinity with collaborative learning educational innovation or technology-enhanced learning.
• Strong communication and academic writing skills in English.
• Ability to work independently as well as in a collaborative interdisciplinary research team.

Conditions of Employment

A meaningful job in a dynamic and ambitious university in an interdisciplinary setting and within an international network. You will work on a beautiful green campus within walking distance of the central train addition we offer you:

• Full-time employment for 45 years (54 months) with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme paid pregnancy and maternity leave partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities scale P (min. 3059 max. 3881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure on-campus childrens day care and sports facilities.
• An allowance for commuting working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information

Do you recognize yourself in this profile and would you like to know more Please contact the hiring manager dr. Karolina Doulougeri ().

Visit our website for more information about the application process or the conditions of employment. You can also contact .

Are you inspired and would like to know more about working at TU/e Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae including the contact information of three references.
• A statement of research intent outlining your proposed theoretical and methodological approach to answer the central research question (500-800 words)

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until 29th October 2025. Interviews will be conducted on Friday 7th of November 2025.

Starting date: as soon as possible (no later than 1st January 2026).

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check please consult Chapter 8 of theNational Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.