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Research Fellow in AI and Financial Computing
2 months ago
We are seeking a highly skilled Research Fellow to join our team at the University of Edinburgh's School of Informatics. The successful candidate will work on a project focused on NLP and large language model-based financial asset management and decision support systems.
About the RoleThis is a fixed-term position for 24 months, and the candidate will be responsible for undertaking original research in AI-driven Financial Computing. The project aims to improve our understanding of potential risks and uncertainties in financial asset management, unlocking significant improvements in finance investment management and decision-making.
Key Responsibilities- Conduct original research in AI-driven Financial Computing, collaborating with the School of Mathematics and the Centre for Investment Innovation.
- Develop and implement large-scale NLP models for financial text analysis, using techniques such as BERT and GPT.
- Work with industry collaborators, particularly in the finance sector, to apply AI and NLP models to real-world problems.
- Contribute to the development of benchmarking methods to evaluate AI/NLP/LLM models against state-of-the-art AI models and evaluation metrics.
- PhD in Finance, AI/NLP, or a related field, with experience in quantitative finance or financial computing.
- Proven experience in undertaking original research with a strong focus on financial asset management, portfolios, or price forecasting.
- Strong relevant research skills in running large-scale NLP models, including experience with software development and experiment testbeds.
- Effective written and oral communication skills, with experience in research presentations and publications.
- Experience in contributing to the supervision of undergraduate and postgraduate students, as well as engaging with wider research and industry communities.
- Proficiency in Linux, physics simulators, and ROS1/ROS2.
- Experience in applying foundation models in computer vision.
- Background in Soft/Flexible Robotics.