PhD Position Foundation Models for Industry (FIND)

PhD Position: Foundation Models for Industry (FIND)

Foundation Generative AI Models enable the next wave of intelligent automation across numerous industries. This project develops scalable multi-modal models and translates them into real-world systems.

Job description

Foundation Models lie at the core of today’s Generative AI revolution, enabling systems that can learn from massive, heterogeneous data, generalize across tasks, and empower increasingly autonomous and adaptive technologies. They are transforming how we approach complex cognitive tasks, from perception and reasoning to generation and decision-making, and are rapidly becoming the backbone of next-generation industrial AI. Within the NWO Perspectief program Foundation Models for Industry (FIND), this PhD position aims to advance multi-modal foundation models that operate across diverse industrial data types, including vision, radar, text, multi-spectral satellite imagery, and molecular data, and translate them into real-world impact in domains such as Electric Mobility and Robotics, Molecular Discovery, Smart Industry, and Remote Sensing.

The project will explore both large-scale pre-training and adaptation of foundation models on high-performance computing (HPC) infrastructures, as well as the development of efficient, robust, and compressed architectures that can be deployed on edge devices, embedded platforms, and autonomous systems. A central goal is to create a seamless bridge between scalable, compute-intensive generative models and efficient, real-time AI systems suitable for robotics, intelligent vehicles, industrial automation, and emerging Agentic AI applications.

The PhD candidate will contribute to the development of the FIND open, precompetitive toolbox of models, training methodologies, and integration strategies, helping to extend foundation models to industrial use-cases that are currently underserved. Embedded within a unique national consortium including universities such as TU Delft, TU Eindhoven, University of Amsterdam, and Leiden University, and industry partners such as ASML, NXP, Shell, and Canon, the candidate will collaborate closely with academic and industrial partners, participate in co-designed use-cases, and benefit from cross-disciplinary exchange and industry internships. This position offers a rare opportunity to shape the future of foundation models that not only scale in capability, but also translate into resilient, trustworthy, and deployable AI solutions for the high-tech industries of tomorrow.

Job requirements

1. An M.Sc. degree in computer science (preferred), electrical engineering or relevant fields
2. Strong background in computer science, optimization and advanced algebra
3. Background in Deep Learning, Generative (and Agentic) AI is prefferable
4. Track record of publication in venues of AI is a big plus
5. Experience in software engineering and programming with Python / Pytorch
6. Good verbal and written English skills
7. Excellent communication and interpersonal skills and ability to work in a collaborative environment

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.