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Field
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within the climate change domain. The techniques are based on statistical and computational approaches, including machine learning algorithms. The project aims first to contribute to the prevention of fake
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to implement for the entire network. To address these challenges, the project aims to develop a novel, population-based indirect damage identification system, leveraging data collected on instrumented railway
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for Smart Cities of Tallinn University of Technology (TalTech) invite applicants for a 4-year PhD position in the field of responsible AI governance for smart city development. The project focuses on how
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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Job Description The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 2 months ago
systems. Key Responsibilities Develop graph-based (multi-)omics analysis algorithms Benchmark graph-theoretic against graph-ML approaches Analysis of food-related (multi-)omics data Your Profile The ideal
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maintaining human oversight for quality and accuracy. This real-world case provides a unique opportunity to study how trust in AI systems develops, whether specialists seek to preserve authority in decision
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learning, with a particular focus on differential equation-driven frameworks. The research will be fundamentally oriented, and the overall mission is to develop computationally efficient and statistically