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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 5 hours ago
improve estimation of rates of snow accumulation, snowmelt, ice melt, and sublimation from snow and ice worldwide at scales driven by topographic variability. We seek projects focusing on the use of machine
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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In
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postdoctoral researcher to join the ERC Pandora project team. Your work will involve analyzing or designing models of surface processes to estimate their role in the formation of environmental refuge zones
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of models of co-infection (including parameter estimation, model calibration, validation, etc.) and close collaboration with researchers, clinicians, and public health partners. Professor Hollingsworth’s
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tap density and material quality. Develop an advanced optimization and sensitivity analysis framework for accurate parameter estimation. Produce research publications in high-impact journals and
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, fined tuned for zooming in on machine spatial reasoning, is within the scope of this project. Developing efficient algorithms for converting computer simulations of a system in a complex environment (e.g
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-phase flow behavior and mixing within the CSTR. These simulations will be used to evaluate impeller performance, analyze hydrodynamic characteristics, and identify key synthesis parameters influencing
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with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation Implementing machine learning approaches that preserve physical constraints while handling
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manufacturing process, such as: Identify any key parameters in the mfg process that impact material performance Optimise power/energy usage throughout the process The outcome will be to optimise the manufacturing