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, SNA, Machine Learning, Sentiment Analysis) with qualitative ones (digital ethnography, narrative analysis). One of the tangible side-effects of the project will be developing research tools for Polish
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on food craving and health-related decision-making. To this purpose, we will use a combination of brain imaging, behavioral measures, and machine-learning techniques. Activities The successful candidate
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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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of this annex, as well as to: Programming in Python and R. Statistical classification and machine learning methods: SVM, neural networks and logistic regression. 3.2. Qualification: Official Master’s degree in
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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engineering Engineering » Computer engineering Engineering » Knowledge engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Portugal
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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-engineering-and-automation/nonlinear-systems-and-control ) at Aalto University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as