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Field
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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of dynamic outdoor thermal comfort. This objective aims to reduce the computational demands of microclimate simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven
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(Berlin) in a close partnership with the Forschungszentrum Jülich, contributing to algorithm development, computational tool implementation, and validation with experimental partners (TU Graz and
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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-enabled adaptation. The aim is to develop theoretically grounded yet practically deployable algorithms that allow multi-agent robotics to operate robustly in dynamic, uncertain, and interactive environments
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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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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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region of Portugal, although other tasks may be considered according to the profile of the recruited researcher. The researcher will be responsible for implementing spatial analysis algorithms, developing
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create