PhD on Multi-modal Open-Source Foundation Models

Introduction

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!

Job Description

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.

Job Requirements

• A master’s degree (or an equivalent university degree) in Computer Science or a related field.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Experience in programming and empirical analysis in Deep Learning (e.g. in Python, PyTorch). 
• Excellent problem-solving skills and ability to work independently and collaboratively.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

• A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you: 
• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).  
• A year-end bonus of 8.3% and annual vacation pay of 8%. 
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. 
• An excellent technical infrastructure, on-campus children's day care and sports facilities.  
• An allowance for commuting, working from home and internet costs. 
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. 

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Joaquin Vanschoren, Associate Professor, j.vanschoren@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Anna Vettoruzzo, Postdoctoral researcher, a.vettoruzzo@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.