29 distributed-algorithm-"Fraunhofer-Gesellschaft" Postdoctoral research jobs in Germany
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- Technical University of Munich
- Forschungszentrum Jülich
- Nature Careers
- Leibniz
- University of Tübingen
- Fraunhofer-Gesellschaft
- Max Planck Institute for Astronomy, Heidelberg
- Max Planck Institute for Brain Research, Frankfurt am Main
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
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Southeast Asia) are welcome. Your Future Tasks: Engage in interdisciplinary research focused on mantras and/as sound, and mantras as unequally distributed sounds. Publish your findings in peer-reviewed
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Research profile in machine learning (e.g. robustness, out-of-distribution/anomaly detection, fairness, explainability, uncertainty quantification) or AI applications in the healthcare domain Interest in
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of how hotspots in human and marine mammal presence are distributed in affected areas. Acoustic ship models will furthermore help to understand and gauge the acoustic footprint of ships in various types
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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MesaPD to solve complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms
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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination