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multiscale analysis of the mass distribution, as well as that of the flow field structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer
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of biased decision-making in machine learning (ML)? This PhD position offers a unique opportunity to contribute to cutting-edge research in algorithmic fairness, ensuring that automated decision-making
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discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Swarm intelligence Algorithmics Parallel
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Computer Science, Civil Engineering, or any related engineering discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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industrial partners and is partly externally funded by the KK Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools
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, including local hydrogen and electricity markets, but also flexibility markets related for managing network congestion. Some specific topics that are relevant for this PhD position include (non-exclusive list
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for these new solution methods will be derived. This position is part of a larger research project “Discrete Decision Making under Uncertainty”, in which researchers work on developing new theory, algorithms, and
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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and algorithms for efficient deep-tissue energy transfer. Experimental Validation – Integrating and testing prototypes in realistic laboratory and clinical settings to demonstrate safe and effective