Foundation Generative AI Models enable 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- An M.Sc. Degree in computer science (preferred), electrical engineering or relevant fields
- Strong background in computer science, optimization and advanced algebra
- Background in Deep Learning, Generative (and Agentic) AI is prefferable