Postdoc in Neuro-Symbolic Methods Integrating Generative AI with Symbolic Reasoning

Short introduction

Are you fascinated by a future where generative AI models fully comply with the specifications and the requirements of the systems that use them? We are excited to offer a postdoc position, which is focused on integrating generative AI (e.g., LLMs) with symbolic reasoning, where the latter can verify the output of the former is compliant with explicit and formal system constraints. The position is within the context of the EU-funded SmartEM project, which aims to use AI-assisted methods to create industrial surrogate models from heterogeneous data sources. In SmartEM, we you will have the possibility to directly collaborate with industry partners such as Canon, Philips, ThermoFisher, Siemens and others.

Job Description

Large Language Models are known to hallucinate. Techniques such as In-Context Learning, Retrieval-Augmented Generation, Chain-of-Thought Prompting, and Self-Refinement can help reduce hallucinations, but they do not eliminate them entirely. This poses a challenge in applications where trustworthiness and reliability are critical.

In this project, you will explore neuro-symbolic methods that integrate LLMs (or Generative AI more broadly) with Symbolic AI techniques. In this hybrid approach, the Generative AI component proposes candidate solutions to a problem, while the Symbolic AI component validates these solutions against explicit, formalized constraints by symbolic reasoning. An example is a LLM translating natural language specification into a symbolic representation (e.g. knowledge graph (KG) or logic program) and a symbolic solver computing the solution. Another example is the generation of surrogate model architectures for complex industrial systems: the generative component proposes models based on natural language specifications, while the symbolic component ensures compliance with system constraints, encoding domain knowledge and business requirements, provided in symbolic form.

The research will be conducted in collaboration with industrial partners as part of the European project SmartEM, focused on surrogate modeling. The goal of SmartEM is to develop surrogate models, or systems of surrogates, for complex industrial systems or their high-fidelity simulations. The European project will supply concrete, real-world applications to validate and refine the general methods developed during the Postdoc research.

You work will take place within the Interconnected Resource-aware Intelligent Systems (IRIS) cluster at the Mathematics and Computer Science department. The research topic will be tailored to your research interests. The project offers collaboration with industrial partners, providing a chance to test your models in real-world scenarios. You will also have the chance to closely collaborate with a SmartEM PhD candidate.

Job Requirements

• Motivated researcher, with a PhD and/or Master’s degree in data science research, or a comparable domain.
• A strong background in machine learning (specifically generative models) and/or symbolic reasoning.
• Ability to conduct high quality academic research, reflected in demonstratable outputs.
• A team player who enjoys coaching PhD and Master's students and working in a dynamic, interdisciplinary team.
• A proven ability to manage complex projects to completion on schedule.
• Excellent (written and verbal) proficiency in English, good communication and leadership skills.

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 1 year with a possible extension of 6 months. (NB. there is financial coverage for 1 year and 6 months, after 1 year a standard evaluation will be made for continuation tot the 6 months.)
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. € 3,881 max. € 5,538).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs. 
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.

Information and application

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. See the video.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Tanir Ozcelebi, Associate Professor, t.ozcelebi@tue.nl or +31 40 247 4426.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services, hrservices.mcs@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 using the apply-button. The application should include a:

• A research statement, including research experience and interests, and a short outline of the preferred future research direction (max. 1 page).
• Curriculum vitae, including education history, relevant courses and theses, research experience, full list of publications, and teaching experience (if available).
• Electronic copies of (or links to) PhD and Master theses.
• Electronic copy of publications (if more than 3, please submit top 3).
• Contact details of 2 referees.

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.