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retrieve shapes, overlay errors, and other geometrical parameters of the target using methods ranging from local and global optimizers to priors and neural networks developed by partners in the project. Job
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selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing
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, including physics-informed neural networks, neural operators, hybrid physics-ML approaches, and emerging foundation-model paradigms for scientific data. Scientific machine learning is increasingly important
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Description Do you wish to join the new Marie Sklodowska-Curie Action Doctoral Network PREFERENCE and help us make a transformative difference in the field of molecular imaging? Then, apply to join the
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to platform chemicals and fuels making use of dynamically operated processes. This is a promising route to alleviate net congestion and make more effective and economic use of renewable electricity without
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, targets the conversion of intermittent electricity to platform chemicals and fuels making use of dynamically operated processes. This is a promising route to alleviate net congestion and make more effective
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of the way. With 3,200 m² of state-of-the-art lab facilities, housed in a museum with more than 40 million natural history objects, dedicated mentorship, and access to our broad international network
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closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally. Click here to go to the website
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Welcome to Maastricht University! Join a public-private partnership working on the development of humin based recyclable networks for adhesive and composite applications. In this PhD project, you
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complex dynamic system. Minor disruptions can lead to major delays with traffic jams spreading like oil spills over entire networks. We believe traffic management based on reliable predictions is therefore