Research Associate

Fixed term: For 24 months

The School of Informatics, University of Edinburgh invites applications for Research Fellow in NLP and large language model-based financial asset management and decision support systems.

The Opportunity:

A post-doctoral fellow on AI, NLP and financial computing will be recruited for 24 months for assisting with the execution of the project. The candidate will undertake original research in AI-driven Financial Computing, within the School of Informatics in collaboration with School of Mathematics and the Centre for Investment Innovation.

The project RA improves a deeper understanding of potential risks/uncertainties to which firm-based - risk factors are measured, hence unlocking the potential for significant improvements in the fields of finance investment management, and decision-making.  The project will also aim to provide suitable benchmarking methods to evaluate our proposed AI/NLP/LLM models against commonly used and state-of-the-art AI models as well as evaluation metrics.

Your skills and attributes for success: 

• PhD and experience in Finance. AI/NLP Large Language Models (GPT) or Quantitative Finance/Financial Computing background(e.g. ChatGPT for asset risk management). Candidates who are close to completing their PhD, and who otherwise meet the selection criteria, will be considered.
• Proven experience of undertaking original research with a strong focus on financial asset management, portfolios or price forecasting.
• Proven experience of work with industry collaborators, particularly related to finance sectors.
• A track record of first author and/or collaborative publications in high quality journals and international conferences (Finance, AI, NLP related publications).
• Strong relevant research skills in running large scale NLP models (e.g. BERT, GPT) for financial text analysis. The candidate shall have strong research skills of using LLM-based models for firms financial Information summary.
• Strong software (e.g. Python, Pytorch and relevant GitHub packages) and experiment testbed development experience (e.g. benchmarking NLP/ML models, using ChatGPT for document analysis, financial asset price forecasting). The candidate shall have experience in benchmarking and software implementation prototype.
• Effective written and oral communication skills in a range of contexts (e.g. research presentations and publications).
• Experience of contributing to co-supervise UG/MSc students as well as in more specialist areas of AI/NLP and Financial Computing.
• Experience of engaging with a range of wider communities such as financial industry sectors, asset management firms and wider research/industry communities.

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