I am in the midst of a PhD in computer science and need a knowledgeable research assistant to keep my alert-correlation work on track. The thesis treats alert correlation first and foremost as a research problem, so every choice—from literature curation to experimental validation—has to be academically sound and publication-ready. Where I need you most is guidance: I already run the day-to-day experiments, but I want a senior mind to challenge assumptions, suggest sharper methodologies, and steer the project away from dead ends. In particular, I am weaving an AML-based approach into the correlation logic and need help ensuring that the design, implementation, and data interpretation stand up to rigorous peer review. Key deliverables I will look for • A well-structured and continually updated literature matrix with critical annotations • Methodology reviews that translate high-level goals into reproducible experiments • Feedback memos on each draft chapter, with special focus on the AML sections • A final pre-submission audit covering argument flow, statistical validity, and citation accuracy We can meet weekly over Zoom or a similar platform, and I am happy to share my current code (Python, scikit-learn, Jupyter) and datasets so you can dive straight into the details. If you have a strong publication record in alert correlation, IDS, SIEM, or related network-security analytics, I would love to collaborate with you and push this research to a defendable finish.