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in terms of detection accuracy and reliability Your Profile Ongoing masters degree studies in computer science, data science, engineering, machine-learning, or other closely related field Good
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programming neural networks, machine learning theory and machine learning software frameworks (e.g., PyTorch or JAX). Curiosity-driven personality with the ability for creative and analytical thinking
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relies on three pillars: Optimal control theory , Machine learning and neural networks, Closed-loop control theory. While optimal control tools enable the description of optimal collision avoidance
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applications and algorithms that can leverage associative memories, including machine learning and LLMs, genomics, and classical data science methods (tree models, decision trees, finite automata). We
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Your Job Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant applications, e.g
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design of hybrid electrical–optical computing architectures and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among
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University. IGE website: https://www.ige-grenoble.fr Activities Analyse and harmonise MOSAiC data to investigate discrepancies between observations and Arctic ozone simulations Use machine learning
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models: deep learning (4D CNNs, Transformers, RNNs) on fMRI and ECoG data Explanatory AI: Applying machine learning models to guide post-stroke neurorehabilitation Predictive AI: Optimizing deep
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advances the progress of research. Your tasks involve: Developing a machine learning-based model to map satellite retrievals to ground based air pollutant concentrations Conducting error assessment on the
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will also support the development of machine-learning models to predict biochar catalytic performance from feedstock composition and preparation conditions. Where to apply Website https