Knowledge Transfer Partnership (KTP) Associate in Artificial Intelligence

This is an exciting opportunity for someone with a postgraduate/doctoral degree in Computer Science, Machine Learning, NLP, Computer Linguistics, or a closely related field. The post holder will lead a cutting-edge innovation project that aims to revolutionise the non-catastrophe insurance market by leveraging LLMs to streamline and enhance the efficiency of data management and analysis. Based at Howden Re, the fastest growing reinsurance broker, the KTP Associate will develop and deliver a state-of-the-art LLM-driven automated workflow for data profiling in the reinsurance industry.

The objectives of the project include:

1: Developing and fine-tuning an automated pipeline for extracting semi-structured and unstructured data using LLM-based methods.

2: Extending the pipeline to support multilingual and regional applications.

3: Creating a user-friendly interface that makes advanced tools accessible to non-expert users.

Plus, the successful candidate will be part of the prestigious 50-year-old national Knowledge Transfer Partnership programme offering a dedicated professional development budget, a network of fellow Associates from many disciplines, and training and mentoring opportunities. The Associate will also have the opportunity to write publications about their work alongside the academic and company teams.

Salary details: The post is offered with a salary on UCL Grade 6B with a salary starting at £38,607 pa (including London Allowance)

Appointment at Grade 7 is dependent upon having been awarded a PhD and will be offered with a starting salary of £44,840 pa (including London Allowance)

We expect the appointed candidate to start in July 2025

Please include a supporting statement outlining your qualifications and experience, and explaining how they make you a suitable candidate for the position. Also, a curriculum vitae, including a list of publications (if available) and links to GitHub, GitLab, or other repositories showcasing relevant work (if applicable).

If you need reasonable adjustments or a more accessible online format to apply for this job, please contact mgmt.-hrsom@ucl.ac.uk

For informal enquiries about the role, please contact Dr Deyu Ming (deyu.ming.16@ucl.ac.uk)

The project aims to leverage Generative AI (GenAI) to streamline and enhance the efficiency of data management and analysis. Combining cutting-edge Large Language Models (LLMs) with a robust workflow for data extraction, translation, and analytics, to reduce manual data processing requirements, enable near real-time pricing and aggregation.

Key objectives include developing an automated pipeline for extracting semi-structured and unstructured insurance data, fine-tuning LLMs for multilingual and regional applications, and creating a user-friendly interface and database for storing the structured data.

This project will deliver tools that enhance transparency and efficiency during the (Re)insurance placement process.