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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus
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Researcher for the Mechanical Systems Modeling (MSM) Group. The Electric Motor Researcher will conduct detailed analysis of electric motors and motor drive systems used in gas centrifuge applications
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require additional information? Please contact: Efstratios Gavves, Associate Professor, e.gavves@uva.n Where to apply Website https://www.academictransfer.com/en/jobs/359154/postdoc-on-robot-world-models-u
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patients with early DKD and matched healthy controls. ▪ Development of an AI-driven digital African twin model capturing population-specific molecular heterogeneity, disease trajectories, and predictive
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experimentation, modelling, and noise‑control strategies across systems such as airfoils, ducted propellers, drones, and wind‑energy devices. With strong academic and industry partnerships, our group tackles
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 months ago
control, and coronagraph system modeling. Location: Ames Research Center Moffet Field, California Field of Science:Planetary Science Advisors: Natasha Batalha natasha.e.batalha@nasa.gov 650-604-2813 Ruslan
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financial planning and predictive modeling to inform strategic growth, program viability, and resource allocation. Set Continuum-level financial targets and guardrails (e.g., administrative budgets, reserves
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Optimization (AI/ML) Developing AI/ML models to predict drillability issues based on mechanical rock properties Real-time parameter optimization (WOB, RPM, flow rate, etc.) using machine learning techniques