Research Intern – Explainable Ai And Reporting Framework For Power Grid Machine Learning Applications
HITACHI ENERGY CANADA INC.
Saint-Laurent, Canada
Hybrid
Ml explainability and trust-building
Model transparency, reproducibility, traceability
Python and ml libraries
The intern will contribute to the design and evaluation of explainability and governance-aligned reporting frameworks for machine learning models used in power grid applications
Job Summary
The intern will contribute to the design and evaluation of explainability and governance-aligned reporting frameworks for machine learning models used in power grid applications.
Responsibilities include conducting literature reviews, investigating frameworks for model transparency, and exploring explainability methods like SHAP and LIME.
This is a remunerated internship with a flexible start date, held in a hybrid format or remotely within Canada.
Matching Summary
The intern will contribute to the design and evaluation of explainability and governance-aligned reporting frameworks for machine learning models used in power grid applications.
Skills & Requirements
Must-have
ML explainability and trust-building
model transparency, reproducibility, traceability
Python and ML libraries
research experience
hybrid work mode
Nice-to-have
critical and innovative thinking
taking lead in realizing ideas
AI governance frameworks
first-authored publications
Key Requirements
PhD students/candidates or senior master's students