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of accelerating discovery across the life sciences. We are seeking a highly skilled AI Research Engineer to join our team and advance our AI-driven scientific initiatives. You will build methods for supervised
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skilled Data Engineer to drive scientific innovation through robust data infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi
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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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, 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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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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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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mouse models, in close collaboration with the Bentires Lab at the University of Basel. This PhD project is fundamentally driven by hands-on experimental in vivo mouse work; therefore, candidates must
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prompts and behaviors that improve administrative efficiency and support faculty and staff adoption. The AI Interaction designer uses knowledge of Large Language Model architectures, prompt engineering