PhD or Postdoc Research Position: Web-Search Enabled LLMs for a Circular EconomyKU Leuven • Leuven, Flemish Brabant, Belgium
PhD or Postdoc Research Position: Web-Search Enabled LLMs for a Circular Economy
KU Leuven
- Leuven, Flemish Brabant, Belgium
- Leuven, Flemish Brabant, Belgium
Über
- Advanced product (re-)identification,
- AI-driven product research and data acquisition, and
- Lifecycle product traceability Functieomschrijving The KU Leuven Life Cycle Engineering research group is expanding its activities at the intersection of re- and demanufacturing and advanced AI. Building on our infrastructure for product identification, computer vision, and lifecycle assessment, we will launch the REINFUSE project in 2026, a four-year Flanders Make SBO project. REINFUSE aims to build the next generation of AI-augmented tools for product (re-)identification, information acquisition, product-data enrichment, valuation, and lifecycle decision support. Diverse inputs, such as product images, OCR text, label images, manuals, and web documents, are to be structured and validated within a product data backbone that supports reuse, repair, refurbishing, remanufacturing, and recycling. The project targets TRL 5 demonstration, combining fundamental research with robust, reusable software demonstrators for industrial validation with 10 Flemish companies active in production, refurbishing, remanufacturing, and online auctions. We are seeking a PhD or Postdoctoral researcher to co-develop web-search-enabled LLM-based enrichment pipelines, schemas, and data-structure logic that form the core of the REINFUSE product-information backbone. This role combines:
- Research: designing, evaluating, and refining methods for multimodal product-data extraction, enrichment, and validation.
- Engineering: building and validating reliable, scalable, and maintainable codebases and pipelines that feed into REINFUSE demonstrators in close cooperation with industrial
- (Co)design and develop the database structures that form the backbone of the product-information layer, ensuring that identifiers, attributes, and derived data are stored, versioned, traced, and validated over time.
- Implement and evaluate the data-enrichment pipelines that use web-search-enabled LLMs to extract model- and device-level properties from documents, manuals, and online sources. You will explore versioning strategies, provenance tracking, conflict resolution, and reliability scoring to build a continuously improving product knowledge base.
- Progressively integrate additional input modalities. Initially, image- and OCR-based identifiers are added to the structured database and enrichment logic; later, multimodal LLM-inferred attributes will be added. You will ensure that these inputs are reconciled, validated, and used to enhance product identification and valuation.
- Develop multimodal pipelines combining images, OCR text, free-text descriptions, and web-retrieved documents into structured product properties.
- Support the preparation and organisation of demonstrators and be involved in on-site user tests.
- Support the guidance of master's theses and job students supporting the validation cases and interface development.
- Present research results at (international) conferences and events.
- Assist in workshops, dissemination activities, and teaching tasks (for PhD researchers only at less than 10% of working time).
- You hold a Master’s degree obtained with cum laude or equivalent.
- You have strong programming skills, especially in Python, and are comfortable working with Git and API tooling, such as Postman.
- You have experience in machine learning, NLP/LLMs, multimodal systems, computer vision, or scraping.
- Having experience in data science with SQL or an ORM framework for designing and querying structured data is a strong asset.
- Experience developing software in a team environment and familiarity with collaborative development workflows (version control, code reviews, documentation) are a plus.
- You communicate effectively in English (oral and written); Dutch is an advantage, but not required.
- You hold a PhD in Engineering, AI, Data Science, or related fields with a high relevance to the project activities.
- You bring significant prior relevant experience, such as:
- Designed complex data structures or schemas for real-world use,
- Deployed and maintained web-searched LLM systems,
- Built scalable data ingestion or enrichment pipelines
- A position in a leading research group with a strong international track record in applied research deploying AI in reuse, repair, remanufacturing, and lifecycle engineering.
- Access to large real-world datasets and collaboration with companies across multiple product sectors and active in different product lifecycle stages.
- A research trajectory that blends scientific publication with real-world impact, supporting both academic excellence and industrial relevance.
- For PhD researchers: the opportunity to complete a PhD in a highly relevant industrial–academic environment.
- For Postdoctoral researchers: the opportunity to grow into a technical leader in a strategic Flemish research and innovation project funded through Flanders Make.
- Competitive salary and employment conditions according to KU Leuven standards.
- An attractive working environment and up to 1 day per week home office
Sprachkenntnisse
- English
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