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Field
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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the partner teams and a theory/experiment dialog will allow to enrich the project. The person recruited will have the opportunity to use a large panel of theoretical chemistry and molecular modeling methods
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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from computational engineering and computer simulation (such as the finite element method and constitutive materials models) to represent and exploit relationships along the composition-process-structure
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 17 days ago
abstract representations. The FAMIX metamodel of the Moose platform (Anquetil et al. 2020) models software systems as entities (classes, methods, attributes, etc.) and relationships (calls, inheritance
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 22 days ago
fundamental physical mechanisms using computer simulations and the methods of non-equilibrium statistical physics. The Research The PhD student will work under the supervision of Dr. Philip Bittihn within
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, artificial intelligence, and its applications to large scale data domains in science and industry. This includes the development of deep generative models, methods for approximate inference, probabilistic
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Learning 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
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of microstructures, physics-oriented microstructure descriptors discovery based on the use of RRAE (rank reduction autoencoders) and neural operator approaches designed to approximate the solution of complex