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Term: Initially 1 year, renewable. Appointment Start Date: As early as February 2026, but flexible Group or Departmental Website: https://med.stanford.edu/bridge-lab.html (link is external) How to Submit
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Systems and Control division focusing on data-driven control methodologies. About the research project Model-based control is arguably the prime framework to perform certifiably-safe regulation of dynamical
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and uncertainty (e.g. demand evolution, renewable generation) influence system performance and trade-offs. The research will combine analytical modelling with data-driven and AI-based methods
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, machine learning, and data-driven modeling methods, physiology, transport, fluid and solid mechanics, systems analysis, circuit prototyping, technology transfer, and biomedical design practices, in
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Environment Water Research Centre (EEWRC) The Climate and Atmosphere Research Centre (CARE-C) The Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC) Considerable cross-centre
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Scholar (FP01) – AI Imaging & Retinal Disease who is interested in ophthalmology to assist in refinement of AI models as well as validation of new biomarkers and data analysis to be able to predict whether
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Engineer to support and lead projects within the Assured Communications and Electromagnetic Dominance (ACED) technical thrust area. This position focuses on the design, simulation, prototyping, and testing
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to: Develop mechanistic and data-driven models to analyse concentration–response relationships and biological readouts from advanced in vitro assays Apply statistical and computational methods to quantify
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flexible role not tied to any single predefined project. The successful candidate will contribute to a range of modelling-driven projects that tackle key questions in cancer biology, such as understanding
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of internationally visible, foundational research in AI-driven semantic structure extraction, automated reasoning-flow modeling, and adaptive content generation. The research focuses on methods for analyzing and