Location: | Edinburgh, Hybrid |
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Salary: | £39,347 to £46,974 per annum (Grade 7) |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 10th July 2024 |
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Closes: | 31st July 2024 |
Job Ref: | 10892 |
Full Time - 35 hours per week
Contract type - Fixed term - 24 months
Start date: ASAP or by mutual agreement
We are looking for an exceptional candidate to join the School of Mathematics at the University of Edinburgh to conduct research on the use of generative machine learning models and synthetic time series data with applications to Finance.
This post is advertised as full-time (35 hours per week). We are open to considering requests for hybrid working (on a non-contractual basis) that combine a mix of remote and regular on-campus working.
The post is subject to Level 4 pre-employment screening - PES4 Enhanced Check
The Opportunity:
The project falls under a partnership between NatWest Group and the University of Edinburgh and seeks to develop tailor-made synthetic data generation that can be used for solving the following challenges:
The objective of this project is to understand the appropriate balance between privacy, fidelity and utility of synthetic data for applications such as Credit Risk and Pricing. This will require the development of novel algorithms and approaches for (conditional) time-series data generation. The candidate will be working with Professor Lukasz Szpruch (University of Edinburgh and The Alan Turing Institute ) and Data Scientists at NatWest Banking.
Your skills and attributes for success:
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