We are recruiting for a PhD candidate to join our team working at the forefront of large language models (LLMs), diffusion models, and generative AI. The successful candidate will develop novel architectures, training strategies, and evaluation frameworks for foundation models, with applications spanning but not restricted to scientific and biomedical domains.

You will explore cutting-edge topics such as multimodal learning, controllable generation, reasoning, efficient fine-tuning and inference. The research may involve building and analysing generative models for structured data, text, images, or scientific sequences, as well as investigating how these models can support discovery and decision-making in complex, high-stakes environments.

As part of our broader research portfolio, you will also have the opportunity to contribute to an interdisciplinary Horizon Europe project focused on AI-driven biomanufacturing. This offers a unique setting to translate generative AI methods into real-world scientific workflows, working alongside biologists, clinicians, and engineers. Domain knowledge of such specific applications isn’t mandatory.

We welcome applicants with strong backgrounds in machine learning, deep learning, natural language processing, computer vision, or related fields. Experience with training or fine-tuning LLMs or diffusion models, working with large-scale datasets, and scientific programming is highly desirable.

This position offers an excellent environment for academic growth, international collaboration, and impactful research at the interface of AI and science.