ABOUT THE DIN

NSW Police Force
Knowledge Extraction from Unstructured Text with Large Language Models

Duration: 3-months
Start Date: November 2025
Location: Parramatta
Scholarship: $20,000

About the Company

The New South Wales Police Force is the primary law enforcement agency of the state of New South Wales, Australia. Divided into Police Area Commands (PACs), for metropolitan areas and Police Districts (PDs), for regional and country areas, the NSW Police Force consists of more than 400 Police stations and over 18,000 officers, who are responsible for covering an area of 801,600 square kilometres and a population of more than 8.2 million people.

Project Objective

This project aims to investigate the application of Large Language Models (LLMs) in extracting knowledge from unstructured data and to explore their effectiveness in enhancing policing practices.

Project Tasks

  • Conduct a literature review of state-of-the-art techniques and approaches related to intelligence extraction from unstructured data using LLMs.
  • Prepare and model data for LLM application.
  • Implement techniques to extract intelligence from unstructured text.
  • Evaluate model performance using appropriate metrics and compare it to human benchmarks.
  • Prepare a comprehensive research report documenting the research methodology, findings, and insights. Work on the possibility of disseminating the research findings through academic conferences, workshops, and peer-reviewed journals.

Intern Skills

  • Strong understanding of large language models and generative AI techniques.
  • Experience in data processing and modelling
  • Proficiency in programming languages such as Python
  • Excellent communication skills, both written and verbal, with the ability to document and present research findings
  • Data-driven and research-based mindset
  • Adapt existing skills to new situations
  • Strong teamwork capabilities

Application

Students should fill out an online application form and submit their supporting documents (listed below)  by 14 September 2025.

  • Curriculum Vitae
  • Motivation Letter

 

Our Partner Universities

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