Related skills
python pytorch fraud detection llms agentic ai📋 Description
- Research directions in graph learning for fraud detection (GNNs, graph transformers)
- Design scalable, dynamic, heterogeneous fraud graphs
- Investigate agentic AI and LLM-augmented risk reasoning
- Develop robust learning for adversarial and non-stationary environments
- Empirical evaluation on production-scale datasets
- Translate research insights to system-level implications
- Patent development and submissions to top venues
🎯 Requirements
- Currently pursuing a PhD in CS, ML, statistics, mathematics, or related field
- Strong foundation in graph learning (GNNs/graph transformers)
- Transformer architectures and deep learning
- LLMs and agentic AI systems
- Adversarial, robust, or trustworthy ML
- Demonstrated research capability (publications/preprints)
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