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algorithms for optimal operation of grid-integrated LDES; Develop a co-simulation framework to analyse LDES performance under different grid scenarios. Collaborate with consortium partners to translate
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cell-tracking algorithms, we can follow thousands of individual cells in real time as they respond to carefully designed chemical and mechanical cues. These approaches generate uniquely rich datasets
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Assistant Professor (tenure-track) and Associate Professor (tenured) Positions in Computer Scienc...
of Mathematics and Computer Science (IMADA), and other research sections at the department are Algorithms Computational Science Data Science and Statistics Geometry, Topology and Algebra Learning Experience Design
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, autonomous learning agents are likely to take an active role in human society, engaging in daily interaction and collaboration with humans. Developing learning algorithms that enable these agents to produce
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27.10.2025 Application deadline: 30.11.2025 Are you excited about the possibility to explore ethical, philosophical, legal, epistemic or social implications of using machine learning in different
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credits per year (11-month type) and provides students with learning support services during the assigned period. Lecturers normally teach up to 3 different courses, with each section typically consisting
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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and tools to develop IoT applications, to analyze and design IoT architectures for different application domains, and to develop data analytic tools to analyze the large amounts of data generated by
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) into communication channels to defeat matching algorithms, presentation attack detection, or human reviewers. Protections against these attacks focus on two areas: defending against the injection and detecting
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comparing models with entirely different structures and parameter counts, whether comparing linear regression against mixture models or decision trees. MML is strictly Bayesian, requiring prior distributions