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Field
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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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advanced mathematical frameworks and algorithms that accommodate the distinct operational characteristics of these mobility services while addressing their charging infrastructure needs. Project abstract
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 5 days ago
. Main activities : – Read papers and state of the art - Benchmark existing algorithms – Write problem formulation, proofs of convergence. – Adapt the formulation to the target scenario. – Propose a new
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, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies
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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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are looking for highly motivated applicants with a master's degree in evolutionary biology, population genetics, or conservation genetics. In addition to an interest in evolutionary and conservation biology
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strong background in mathematics and statistics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience, as well as skilled
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework
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agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and behavioral well-being, particularly among vulnerable populations. Applicants are encouraged to approach