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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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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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available in the further tabs (e.g. “Application requirements”). Programme Description The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with
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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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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
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your local Mitacs advisor for details, before starting to develop a project. Quantum stream: Open to all Canadian universities. The project must be in the quantum sector (includes but not limited
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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Science Center has an opening for a graduate student researcher in Mathematical Optimization for large-scale power systems planning. They will deploy developed optimization algorithms on DOE high
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling