Research Intern – Explainable AI and Reporting Framework for Power Grid Machine Learning Applications job opportunity at Hitachi.

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Hitachi Research Intern – Explainable AI and Reporting Framework for Power Grid Machine Learning Applications
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loacation Toronto, Ontario, Canada, Canada
loacation Toronto, Ontar..........Canada

Location: Toronto, Ontario, Canada Job ID: R0116509 Date Posted: 2026-01-19 Company Name: HITACHI ENERGY CANADA INC. Profession (Job Category): Administration & Facilities Job Schedule:  Full time Remote: Yes Job Description: French version follows The Opportunity Hitachi Energy is seeking a highly motivated Research Intern to contribute to the design and evaluation of explainability and governance-aligned reporting frameworks for machine learning models used in power grid applications. The hired intern will work under the supervision of Research Scientist(s) in the Hitachi Energy Research center . This position will be held in a hybrid-format or remotely within Canada. Duration of internship : 4 months (can be extended up to 6 months as per need) Start date : May 4, 2026 (flexible) Mode of work : Remote or Hybrid (flexible) Renumerated Internship How you’ll make an impact Conduct literature reviews and comparative evaluations on ML explainability and trust-building techniques. Investigate frameworks for model transparency, reproducibility, and traceability. Explore and evaluate explainability methods (e.g., SHAP, LIME, surrogate models) and their applicability to industrial ML workflows. Prototype research concepts using Python and modern ML tooling. Document findings and present them in technical reports or publications, as appropriate. Your background PhD students/candidates in Computer Science/Engineering, Machine Learning, Software/Electrical Engineering. Excellent senior master’s (thesis-based) students with relevant experience are also welcome to apply. Solid understanding of machine learning & software engineering concepts, model evaluation, validation pipeline and CI/CD is required. Familiarity with interpretability techniques and/or model governance topics (e.g., explainability, reproducibility, fairness). Proficiency in Python and experience with ML libraries (e.g., Scikit-learn, TensorFlow/PyTorch, SHAP, LIME). Research experience involving defining problems, exploring potential solutions, and analyzing results, with the ability to clearly present findings to key stakeholders. Good communication skills (both written and spoken). Preferred qualification If you have any of the following qualifications, please ensure to clearly mention them in your resume. Prior experience working with interpretability or explainability libraries. Familiarity with AI governance frameworks (e.g., EU AI Act, AI Verify, NIST AI RMF). One or more first-authored publications in top AI/ML conference/journals. Ability to do critical and innovative thinking. Ability to take lead in realizing ideas. Experience with model-driven software engineering. Only selected applicants will be contacted.  ------------------------------------------------------------- Poste: IA explicable et système de rapport pour les applications d'apprentissage automatique dans les réseaux électriques L’offre Hitachi Energy est à la recherche d'un stagiaire en recherche hautement motivé pour contribuer à la conception et à l'évaluation de cadres de rapport alignés sur l'explicabilité et la gouvernance pour les modèles d'apprentissage automatique utilisés dans les applications de réseaux électriques. Le stagiaire recruté travaillera sous la supervision d'un ou plusieurs chercheurs scientifiques au centre de recherche Hitachi Energy. Ce poste sera occupé dans un format hybride ou à distance au Canada. Durée du stage : 4 mois (peut être prolongé jusqu'à 6 mois selon les besoins) Date de début : 4 mai 2026 (date flexible) Mode de travail : À distance ou hybride (flexible) Stage rémunéré Votre impact Réaliser des analyses documentaires et des évaluations comparatives sur l'explicabilité du langage machine et les techniques visant à instaurer la confiance. Étudier les cadres permettant d'assurer la transparence, la reproductibilité et la traçabilité des modèles. Explorer et évaluer les méthodes d’explication (p. ex., SHAP, LIME, modèles de substitution) et leur applicabilité aux flux de travail industriels de l’apprentissage machine. Prototypes de concepts de recherche à l’aide de Python et d’outils modernes d’apprentissage machine. Consigner les conclusions et les présenter dans des rapports techniques ou des publications, selon le cas. Votre expérience​ Étudiants/candidats au doctorat en informatique/ingénierie, apprentissage machine, génie logiciel/électrique. Les étudiants à la maîtrise (avec thèse) ayant une excellente expérience dans le domaine sont également invités à postuler. Une solide compréhension des concepts d'apprentissage automatique et d'ingénierie logicielle, de l'évaluation des modèles, du pipeline de validation et du CI/CD est requise. Connaissance des techniques d'interprétabilité et/ou des questions de gouvernance des modèles (par exemple, explicabilité, reproductibilité, équité). Maîtrise de Python et expérience des bibliothèques ML (par exemple, Scikit-learn, TensorFlow/PyTorch, SHAP, LIME). Expérience de la recherche impliquant la définition de problèmes, l'exploration de solutions potentielles et l'analyse de résultats, avec la capacité de présenter clairement les conclusions aux principales parties prenantes. Bonnes compétences en communication (à l'écrit et à l'oral). Qualifications souhaitées Si vous possédez l'une des qualifications suivantes, veuillez les indiquer clairement dans votre CV. Expérience préalable dans l'utilisation de bibliothèques d'interprétabilité ou d'explicabilité. Connaissance des cadres de gouvernance de l'IA (par exemple, EU AI Act, AI Verify, NIST AI RMF). Une ou plusieurs publications en tant qu'auteur principal dans des conférences/revues de premier plan sur l'IA/le langage machine (ML.) Habiletés à mener une réflexion critique et innovante. Capacité à prendre l'initiative pour concrétiser des idées. Expérience en ingénierie logicielle basée sur des modèles. Seuls les candidats sélectionnés seront contactés.  Qualified individuals with a disability may request a reasonable accommodation if you are unable or limited in your ability to use or access the Hitachi Energy career site as a result of your disability. You may request reasonable accommodations by completing a general inquiry form on our website. Please include your contact information and specific details about your required accommodation to support you during the job application process. This is solely for job seekers with disabilities requiring accessibility assistance or an accommodation in the job application process. Messages left for other purposes will not receive a response. 

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