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Field
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chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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of a diverse set of people from different nationalities, backgrounds, and fields. As a PhD student working with us, you receive the benefits of support in career development, networking, administrative
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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consists of a diverse set of people from different nationalities, backgrounds, and fields. As a PhD student working with us, you receive the benefits of support in career development, networking
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(neural mass models) as well as at the neuron level (neural network models) including plasticity. Electric fields will be estimated based on finite-element method models. The project can be partly adapted
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(dairy and suckler cow) Estimate the net effect of pasture and feed additives on net farm GHG emissions from grazing dairy cows and beef cattle Write and publish scientific articles in reputable
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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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Networking research group at CMI. We are a strong computer engineering environment with close and interdisciplinary collaboration with many different industries. How to apply *** Please apply by submitting
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at the Cyber Security research group and at the Edge Computing and Networking research group at CMI. We are a strong computer engineering environment with close and interdisciplinary collaboration with many
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this gap by developing a machine learning-based downscaling framework that links coarse resolution (0.25°-1°) reanalysis and climate model outputs to fine-scale (∼100 m) estimates of surface melt and