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microdroplets, microfluidic channels and real porous building materials (limestone and sandstone) under controlled environmental cycling that simulates realistic heritage environments. Using advanced imaging and
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-learning–based segmentation, classification and tracking for microbes and microgels in phase-contrast and fluorescence images Optimise these models and pipelines for real-time performance and integrate them
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supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
assimilation Integration (JEDI) framework for atmospheric data assimilation Develop machine learning foundation models based on simulated observations from high fidelity atmospheric simulations for developing
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 month ago
absorption. Developing fast spectral radiance simulation techniques and implementing the observational system simulation experiment (OSSE) based on GISS climate model, which will be applied to research
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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, data-driven control in high dimensions has penetrated many new application areas. Examples include control of autonomous vehicles based on video data, simulation-based prediction of turbulent flows and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 19 days ago
tasks # Performing quantum mechanical and ML-based simulations to determine CO2 adsorption energies # Application of self-consistent continuum solvation models to account for solvation effects
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Offer Description Development of atomistic ab-initio simulations and machine learning models for the study of phonon transport, phase transitions, and structural optimization of phase change materials
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computational science expertise. The Computational Science (CPS) Division focuses on solving the most challenging scientific problems through advanced modeling and simulation on the most capable computers