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of the Biological Carbon Cycle - Combining molecular evolutionary and biochemical approaches, we will generate an integrative, comprehensive understanding of how microbes evolved the ability to capture CO2 billions
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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on quantitative evaluation metrics such as algorithmic fairness paradigms. Applicants should hold a PhD in philosophy, law, cultural anthropology, or (qualitative) social science. The positions are fixed-term (6
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hundred new defense systems have been discovered, many of which are the evolutionary origins of human innate immune systems. Despite these tremendous successes, little is known about how bacteria defend
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Postdoctoral position in Bioinformatics/Computational Biology (m/f/d) (full-time position 100 % ~ 38
package development) and command line-based analysis tools (e.g. Python) • Knowledge with public sequence databases, error correction algorithms • Scientific experience in immunology, molecular and cell
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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Research (SGN), is seeking to fill the following position in the working group of Evolutionary Analyses and Biological Archives, starting as soon as possible: Postdoctoral Researcher in Marine Monitoring
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
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or natural sciences Sound knowledge in machine learning algorithms, statistical methodologies, and biological network analysis Experience with the analysis and integration of transcriptomic and multiomics data