Master Thesis on Large Language Models for Patent Retrieval - Remote

Overview

This internship involves conducting a Master thesis focused on the application of Large Language Models for improving patent retrieval systems.

In Short

• Assess the efficacy of LLM-based rerankers for patent retrieval.
• Research state-of-the-art methods from literature.
• Analyze performance in the context of patent data.
• Implement computational experiments to identify advantages over prior methods.
• Develop novel approaches to address identified limitations.
• Opportunity to participate in publishing work at major NLP conferences.
• Work autonomously and systematically organize tasks.
• Mobile working within Germany is possible.
• Proficient in German or English is required.
• Enrollment at university is a prerequisite.

Requirements

• Master studies in AI, Computer Science, Software Engineering, or comparable.
• Profound knowledge of Machine Learning and Large Language Models.
• Experience in programming with Python and PyTorch.
• Familiarity with Information Retrieval, Linux, and LaTeX.
• Prior knowledge of patents is an advantage.
• Ability to work autonomously and apply analytical thinking.
• Flexible working arrangement within the framework of Smart Work.

Benefits

• Flexible work location (home or Bosch location in Renningen).
• Opportunity to contribute to significant research in AI.
• Diversity and inclusion in the workplace.
• Supportive work environment fostering growth.