Interested in making representation learning and generative models work for structured data (e.g. tables in relational databases) to automatically retrieve relevant insights from data? Then, this 4-year PhD starting Winter 2024/2025 is for you!

Goal of the DataLibra project
Approximately 120 zettabytes of data has been collected worldwide but less than 1% is actually used. Structured data (relational tables and spreadsheets) is prevailing in organizations and typically informs important decisions in e.g., healthcare, governments and finance. Yet, while AI has demonstrated a high impact on applications on text and images, proportional progress on structured data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain, and level of data literacy, get insights from structured data, efficiently, accurately and securely.

Goal of this PhD project

Despite the abundance of structured data, many important insights from this kind of data are left unnoticed as they are difficult to surface or organizations do not have sufficient expertise to extract them. This project will explore emerging paradigms such as table representation learning (TRL), retrieval- augmented generation, generative retrieval, agentic systems, and conversational user interfaces, to automatically surface relevant insights from relational databases and data lakes, in a robust and efficient manner. This PhD project is supervised by Dr. Madelon Hulsebos (CWI) and Prof. dr. Maarten de Rijke (UvA).

What you will be doing

• Develop and execute a 4-year research agenda around insight retrieval from structured data.
• Actively collaborate with other researchers in the DataLibra project (students, PhDs, postdocs,PIs) and external collaborators.
• Communicate research outcomes through papers and presentations at conferences, workshops and other (scientific) gatherings.
• Assist in relevant teaching activities at universities, such as thesis supervision and assisting in courses.

Desired profile

• A master (or equivalent) in computer science or artificial intelligence.
• Self-drive, creativity, rigor, ownership, and excitement to push research in TRL forward.
• Theoretical knowledge of, or experience with, machine learning such as representation learning and generative models, information retrieval, data management, and human-computer interaction.
• Excellent command in English, verbal and written.
• Programming skills, e.g. Python, Java, or C++.
• Prior experience as a research assistant during (under)graduate studies is advantageous.

Diversity code
CWI encourages a diverse workforce: we endeavour to develop talent and creativity by bringing people from different backgrounds and cultures together. We recruit and select based on capabilities and talent. We strongly encourage everyone with the appropriate qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical abilities.

The terms of employment are in accordance with the Dutch Collective Labour Agreement for Research Centres ("CAO-onderzoeksinstellingen"). The initial labour agreement will be for a period of 18 months. After a positive evaluation, the agreement will be extended by 30 months. The gross monthly salary, for a PhD student on a full time basis, is € 2,884 during the first year and increases to €3,801 over the four year period. Employees are also entitled to a holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.33%. CWI offers attractive working conditions, including flexible scheduling and help with housing for expat employees.

Please visit our websites for more information about our terms of employment:
https://www.cwi.nl/jobs/terms-of-employment and
https://www.nwo-i.nl/en/working-at-nwo-i/jobsatnwoi/

Centrum Wiskunde & Informatica

Centrum Wiskunde & Informatica (CWI) is the Dutch national research institute for mathematics and computer science and is part of the Institutes Organisation of the Dutch Research Council (NWO). The mission of CWI is to conduct pioneering research in mathematics and computer science, generating new knowledge in these fields and conveying it to trade, industry, and society at large.

CWI is an internationally oriented institute, with 160 scientists from approximately 27 countries, an informal atmosphere and short lines of communication. We have an activity committee that organizes after-work activities and an informal women’s network.

CWI is located at Science Park Amsterdam, the home of AMS-IX, that is presently developing into a major location of research in the physical sciences in The Netherlands, housing the sciences of the University of Amsterdam as well as several other national research institutes next to CWI.

About the PI’s

Madelon Hulsebos is a tenure track researcher at CWI in Amsterdam. Prior to CWI, she was a postdoctoral fellow at UC Berkeley and obtained her PhD from the University of Amsterdam, for which she did research at MIT and Sigma Computing. Her research interest is generally on the intersection of machine learning and data management, with a focus on developing intelligent systems to interact with structured data. In this context, Madelon founded the Table Representation Learning workshop at NeurIPS and leads various related scientific efforts. She was awarded a BIDS-Accenture fellowship for her postdoctoral research on retrieval systems for structured data at UC Berkeley, and more recently an AiNed fellowship funding her 5-year DataLibra project at CWI.

Maarten de Rijke is a Distinguished University Professor of Artificial Intelligence and Information Retrieval at the University of Amsterdam. His research is focused on designing and evaluating trustworthy technology to connect people to information, particularly search engines, recommender systems, and conversational assistants. He is also the scientific director of the Innovation Center for Artificial Intelligence (ICAI), a national collaboration between academic, industrial, governmental, and societal stakeholders aimed at talent development, research, and impact in AI.