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Field
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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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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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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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, 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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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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-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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21 Nov 2025 Job Information Organisation/Company Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH Research Field Computer science Engineering » Computer engineering Researcher Profile
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24 Nov 2025 Job Information Organisation/Company Computer Vision Center Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country
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control and state (and parameter) estimation algorithms capable of effectively managing corrupted measurement data, communication constraints and modelling uncertainties. You will be joining the team of Dr