Research Intern – Explainable AI and Reporting Framework for Power Grid ML Applications

Line 1: This internship focuses on designing and evaluating explainable AI and governance-aligned reporting for ML models used in power grid applications. Line 2: Conduct literature reviews and comparative assessments of ML explainability and trust-building techniques. Line 3: Investigate frameworks for model transparency, reproducibility, and traceability in industrial ML workflows. Line 4: Prototype concepts using Python and modern ML tooling, including SHAP, LIME, and surrogate models. Line 5: Document findings in technical reports and potential publications, with clear communication to stakeholders. Line 6: Work under supervision in a remote or hybrid setting, with possible extension up to six months.