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validation of linear-scaling electronic-structure and optical-response methods. This includes the advancement and use of efficient algorithms, benchmarking against established approaches, and application
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theory? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a
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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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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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of the screening output. This approach selects new, efficient enzymes, but also generates unique sequencefunction datasets that will be interpreted by regression and tree-based machine learning algorithms to obtain
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successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment
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and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with
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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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-edge academic insight with real-world robotics applications. The PhD project will focus on the design of advanced control and decision-making algorithms to enhance the intelligence, autonomy, and
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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