82 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" "IFM" "IFM" scholarships at Nature Careers
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at the Institute of Medical Informatics within the research group “Medical Data Integration Center (MeDIC)” led by Dr. Michael Storck and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles
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learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another
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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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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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(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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applications of macrosopic quantum coherence in levitated solidstate platforms. Our Team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member
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the Quantum Optics, Quantum Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) - one of the largest quantum hubs in
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advanced data science, using state-of-the-art human stem cell models to uncover previously unrecognized environmental risk factors for Parkinson’s Disease. You will, in close collaboration with a PhD student
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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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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves