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and statistical tools to identify patterns in large datasets The candidates should demonstrate evidence of self-driven and independent research capability, excellent collaboration and communication
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CFD workflows and Lagrangian particle/cell tracking to extracting actionable insights with statistical learning and AI/ML—ultimately enabling more robust scale‑up, smarter process control, and faster
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, supported by a good understanding of urban water systems, water quality, environmental chemistry and statistics. You should have experience in the development and application of water quality models, with
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simulation frameworks. Strong knowledge of probabilities and statistics. Experience in design and deployment of behavioral experiments and/or survey travel data collection in the field. Demonstrated