[Integrated and lightweight photovoltaics]

Facing the challenges of our time

European funding programmes generate vast amounts of information, including funded projects, evaluation criteria, consortium structures, publications, patents and technology roadmaps. However, this information is largely unstructured and difficult to exploit effectively at scale. We are seeking a highly motivated Master's student to develop an AI-powered Funding Intelligence Platform that automatically collects, structures and analyzes European innovation data. The project will combine web scraping, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Knowledge Graphs and Agentic AI to transform fragmented information into actionable insights

Your responsibilities

• Develop web-scraping and automated data collection pipelines
• Aggregate, clean and structure large volumes of heterogeneous data
• Apply NLP and LLM techniques to analyze unstructured documents
• Build semantic search and RAG-based intelligence systems
• Develop Knowledge Graphs linking projects, organizations, technologies and funding programmes
• Design agentic AI workflows for autonomous information gathering and analysis
• Perform statistical, predictive and causal analyses to identify success factors
• Create dashboards and visual analytics tools supporting proposal strategy and consortium building
• Generate actionable recommendations from large-scale funding and innovation data

Currently pursuing or recently completed a Master's degree in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, Statistics, Engineering or a related field