144 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral research jobs in Germany
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Physical Oceanography and Instrumentation, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations works interdisciplinary within a joint research program. What will be your
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Do a PostDoc in Pathology AI! 11.10.2023, Wissenschaftliches Personal The Computational Pathology Lab at the Technical University of Munich (TUM), TUM School of Computation, Information and
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Medicine and Andrology | Institute of Reproductive Genetics We are UKM. We have a clear social mission and, with our focus on healthcare, research, and teaching, we bear a unique responsibility. To meet our
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the study of the impact of digital and computational pathology on clinical workflows and patient care. Our lab is located in the heart of Munich at the TUM Klinikum rechts der Isar (MRI), Institute
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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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-responsive proteins to develop genetic switches and circuits in therapeutically relevant bacteria. Your tasks: Use computational tools to design protein structures with desired properties Produce
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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-pathogenic fungi and identifies targets for the development of novel natural product-based antibiotics. The junior research group (Epi-)Genetic Regulation of Fungal Virulence (https://www.leibniz-hki.de/en/epi
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on Clostridium carboxidivorans and Clostridium ljungdahlii, for which we have already established robust genetic and process engineering platforms. The following publications illustrate the potential and direction
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ljungdahlii, for which we have already established robust genetic and process engineering platforms. The following publications illustrate the potential and direction of our work: Lauer et al. (2022): Metabolic