Graduate PhD Summer Intern – AI/ML Software Developer

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Requirements:

• Only current PhD students will be considered for this internship.
• Experience in deep learning models, Bayesian neural networks, graph neural network models, and probabilistic semantic graphs.
• Experience in the formulation of mixed-integer optimization problems and open-source solvers for sensor placement in distribution systems.
• Demonstrated experience in programming languages such as Python and MATLAB.
• Experience with open-source, collaborative software development and use of tools such as GitHub or GitLab for project management and version control.

Responsibilities:

• Develop sensor placement and optimization software tools for modern distribution power systems integrated with clean energy resources such as Photovoltaics, batteries, EV Charging Stations, and electric vehicles.
• Contribute to the development of deep learning models such as Bayesian neural networks, graph neural networks, probabilistic semantic graphs, and Generative AI to detect anomalies such as missing data, bad data, and communications failure in sensor data.
• Development of data driven forecasting and disaggregation models and validation of both centralized and distributed state estimation algorithms.