PhD on Multi-modal Open-Source Foundation Models

Join a groundbreaking project to develop next-generation, open-source multi-modal foundation models. Collaborate with top research labs and experts to create transparent, efficient, high-performing models with novel capabilities that democratize access to AI. Apply now!

Information
We are seeking a highly motivated PhD student to join our research team in an ambitious 4-year project on next-generation multimodal, open-source foundation models. You’ll be part of an excellent team of scientists, covering the full spectrum from model development to evaluation and real-world use cases.

Snapshot
Artificial Intelligence is reshaping our world. Now you get to shape AI. This large and ambitious project aims to develop advanced, multimodal, open source foundation models based on solid research on model architecture, data quality, scaling, generalizability, finetuning, and safety. The focus is on multimodality aspects, including tabular and time series data, as well as efficient model finetuning. It combines the unique expertise of leading AI companies and top academic labs. This will be an inclusive, community-driven project designed to and foster a new wave of innovation and scientific advancement.

The team
The Automated Machine Learning team at TU Eindhoven focusses on cutting-edge research to advance the capabilities of machine learning models, while also democratizing AI and leveraging it to help humanity. We are a team of scientists and engineers who aim to deeply understand, explain, and build AI systems that learn continually and automatically assemble themselves to learn faster and better. In addition to producing highly-cited research published at top academic venues, we build models and systems that are widely used by people every day. Learn more about us here: https://openml-labs.github.io. This work is part of a large and talented team with world-class labs and experts across Europe, supported by well-known companies with advanced knowledge of LLM development.

The role
We are looking for an exceptional researcher with a real passion for AI, with a deep understanding of the latest developments and eager to explore new avenues of research. In this role, you will design and build cutting-edge methods that will shape the future of foundation models, and that will be deployed in real-world applications. We appreciate a strong empirical and theoretical understanding of deep learning and generative AI.

Key Research Areas:

• Multi-modal foundational model training and in-depth evaluation.
• Transfer learning and model adaptation, especially parameter-efficient finetuning.
• Model finetuning, including human-aligned finetuning (e.g. RLHF), grounded finetuning, and test-time training.
• Model evaluation, especially for new capabilities, generalization performance and model safety.
• Multi-model applications in new modalities including tabular and stream data, also in industry settings.

This research will be performed under the supervision of professor Joaquin Vanschoren, in collaboration with several key European research labs and industrial partners.