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Open Position – Research Assistant
Project Title:
Interpretable Generative AI for Operational and Cyber Risk
Project Summary:
The project aims to develop an interpretable framework for simulating operational and cyber risk losses using GAN-inspired architectures. Unlike traditional GANs, the generator will be a parametric statistical model designed to capture heavy tails and skewness while remaining interpretable and grounded in risk management theory.
Main Tasks:
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Design interpretable generators within a GAN-like setup
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Train and validate models on real-world loss data
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Compare performance with deep learning GANs and classical statistical methods
Candidate Profile:
Strong interest in risk modeling, extreme value theory, or heavy-tailed distributions.
