PhD Position in Tabular Foundation Models for Mixed-Type Data

This PhD position at Inria’s Saclay Centre focuses on advancing tabular foundation models capable of handling heterogeneous data types (numeric, textual, categorical) within a unified architecture. The project aims to address key challenges in integrating diverse data representations into scalable machine learning frameworks. The successful candidate will contribute to open-source software development and publish research findings in top-tier venues. The work aligns with Inria’s mission to drive innovation in digital technologies, particularly in AI and data science. The position offers a collaborative environment within a multidisciplinary research team at the heart of France’s leading tech and academic hub, Paris-Saclay.

• Design and implement next-generation open-source foundation models for processing mixed-type tabular data.
• Develop scalable machine learning architectures capable of handling heterogeneous data representations (numeric, textual, categorical).
• Publish research findings in high-impact academic journals and conferences.
• Contribute to open-source software development, ensuring reproducibility and accessibility of research outputs.
• Collaborate with a multidisciplinary research team at Inria’s Saclay Centre.