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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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level or Engineering Degree in health data science, bioinformatics or biostatistics Expertise in machine learning / deep learning algorithms (supervised and unsupervised methods) Knowledge in diabetes
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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
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Developing statistical, graph, and/or machine learning models to study transaction networks, illicit transaction patterns, and DeFi protocol operations Creating and evaluating tools, documentation, and open
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors
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related field Demonstrated experience in interdisciplinary research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong
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We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific programming for a