PhD position on foundational aspects of foundation models

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.

With over 110 (assistant, associate and full) professors, almost 300 PhD and EngD students, about 1500 Bachelor students and 1000 Master students, the Department of Mathematics and Computer Science (M&CS) is the largest department of the TU/e. By performing top-level fundamental and applied research, and maintaining strong ties with industry, M&CS aims to contribute to science and innovation in and beyond the region.

Introduction

Are you fascinated by how neural networks really work? Are you excited to bridge the gap between theoretical understanding and practical application, translating fundamental insights into tangible improvements for cutting-edge AI systems? Then we have a position for you! We are seeking a passionate and skilled PhD Fellow to contribute to our growing research team, which integrates computer science, physics, and mathematics to tackle challenging questions about the inner workings of neural networks. This position will focus specifically on investigating the inner workings of foundation models.

Job Description

The Role:

We are seeking a highly motivated PhD student to join our team. In this role, you will be at the forefront of research investigating the intricate inner workings of foundation models (including large language models, vision transformers, and potentially multimodal architectures). Your primary objective will be to develop novel theoretical frameworks and empirical methodologies to dissect these complex systems. The ultimate goal is to generate actionable insights that enable the development of FMs that are safer, more robust, and regulation compliant.

About the lab:

Our research group is a growing, multi-disciplinary team dedicated to pushing the frontiers of artificial intelligence understanding. Our core mission is to move beyond black-box approaches and develop a principled understanding of why and how deep learning models, learn, generalize, and sometimes fail. We believe that a deeper comprehension of these systems is paramount to making sure they can be safely applied on society. We are part of the Data and AI cluster at Eindhoven University of Technology, a large, very international group of researchers conducting excellent and internationally recognized research in the fields of data and AI.

The project Context:

This position is embedded within the European collaborative project MedGPT, focused on the development and responsible deployment of foundation models within the healthcare sector. This initiative brings together leading academic institutions and industry partners across Europe, providing additional opportunities for collaboration, knowledge exchange, and real-world impact.

Job Requirements

• A (nearly completed) master’s Degree: a degree in AI, Computer Science, Physics, Mathematics, or a closely related field.
• Passion and Curiosity: genuine enthusiasm for understanding the "why" behind AI and tackling challenging theoretical and practical problems.
• Collaboration skills: ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Mathematical skills: solid foundation in linear algebra and calculus
• Programming Proficiency: strong programming skills, particularly in Python, and experience with major deep learning frameworks (e.g., PyTorch, TensorFlow/Keras).
• Machine Learning Knowledge: good understanding of fundamental machine learning concepts and deep learning architectures.
• Communication Skills: excellent written and verbal communication skills in English (C1 level). Ability to present complex ideas clearly.

Desirable Qualifications:

• Experience with research on Foundation Models (LLMs, Transformers, etc.).
• Expertise in theoretical machine learning (generalization theory, learning dynamics, etc.).
• Experience with large-scale computing environments (HPC, cloud platforms).
• Familiarity with AI safety, robustness, fairness, interpretability, or privacy-preserving techniques.

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 station. In addition, we offer you: 
• Full-time employment for four years, 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. € 2,901 max. € 3,707).  
• 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 children's 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 Hannah Pinson, Assistant Professor, [email protected].

Visit our website for more information about the application process or the conditions of employment.

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 (max. 1 page).
• Curriculum vitae, including a list of your publications and the contact information of a reference (PhD position), 3 references (PostDoc position).

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.