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purpose-driven science and Cornell University’s second-largest college. We work across disciplines to tackle the challenges of our time through world-renowned research, education, and outreach
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of Time • Conduct experimental research, including characterizing mechanisms of plastic and e-waste degradation, genetic modification and engineering of model and non-model microorganisms, designing
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unique biological systems. To achieve this goal, we are mining novel biological systems from databases using AI-driven tools, characterizing their functions through biochemical analysis, engineering them
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experience with process modeling with Aspen Plus Demonstrated experience with statistical analysis (i.e. sensitivity or uncertainty) PhD degree in chemical engineering or related field Preferred Qualifications
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control schemes, embedded-model control, data-driven approaches and robust controller synthesis; Implementation of the selected control methodologies in the high-fidelity end-to-end DFAOCS simulator; Model
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hydrologic and hydraulic models (e.g., WRF-Hydro, HEC-RAS, OpenFOAM, GSSHA, Delft3D, EFDC, etc.). Data Engineering & Computational Workflows – 35% Curate, preprocess, and analyze large environmental datasets
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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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Please apply here: https://apply.workable.com/ellison-institute-of-technology/j/91F1A5719B/apply/ Led by a world-class faculty of scientists, technologists, policy makers, economists and
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oppdatert 24.03.2026 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan inneholde skadelige programmer eller
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, transport processes, numerical modeling, and network theory. Familiarity with plant hydraulics (xylem/phloem transport), osmotically driven flow, and biomechanical modeling. Demonstrated experience in