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integrating IoT systems with cloud platforms such as AWS IoT, Azure IoT, Google Cloud IoT, ThingsBoard, etc. Familiarity with Edge Computing architecture to process data locally before transferring it to
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detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud). Understanding of BMS
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integration. Strong interest in student mentorship and interdisciplinary, applied learning environments. Desirable Qualifications (at least two of the following): Experience with edge/cloud computing platforms
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, or environmental systems. Interest in responsible AI, ethics in machine learning, or interpretable models. Familiarity with cloud-based environments or distributed computing tools (e.g., Spark, Dask, Kubernetes