106 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" PhD positions at Nature Careers
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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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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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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Münster, the CoBIC Frankfurt am Main, the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig and the Johannes Gutenberg University Mainz. RESPONSIBILITIES: Data collection using
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(SNSPD). Additional responsibilities include developing efficient coupling of free-space optics to optical fibers, conducting extended data-taking runs with TES and SNSPD systems, and performing data
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, CRISPR-Cas systems, microRNAs, non-coding RNA, RNA biology of infections, and RNA chemistry. Applicants can choose a mentor who best matches their interests and background (more information under “Panel
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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analysis to extract information on atomic dynamics from image series. Investigate molecular adsorption, surface reconstruction and site-dependent reactivity at the single-atom level Understanding of atomic
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(graduated or close to graduation) in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields. Scientific curiosity and creative thinking
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materials synthesis, advanced operando characterization, and lab scale testing. We use robotic, high-throughput methods, and data science to accelerate novel sustainable materials discovery. PhD Position