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Field
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. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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candidate will develop and conduct empirical research examining human interaction with algorithmic decision-support systems in clinical contexts. The precise focus of the project will be refined
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analyse and develop new, well-founded methods and learning algorithms that extend the boundaries of existing techniques - for example, with respect to expressivity, generalization, interpretability
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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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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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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and algorithms for resource-efficient
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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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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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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