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BUG-ID is a Marie Sklodowska-Curie Doctoral Network project, funded by the European Commission, Horizon Europe Program. Commencing its activities in January 2026, the Network will provide PhD
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DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information Further information may be obtained from
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Deadline : April 15th 2026 · Selection Process : Mai 2026 · PhD Start Date : September-October 2026 How to apply All information are provided on the website of the project : https://www.eu4greenfielddata.eu/
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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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citizens in their choices, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute
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are proud to work together in a truly integrating manner. Our partners, e.g. University of Hamburg, the Max Planck Institute for Meteorology or the German Climate Computing Centre are also hiring. All jobs
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site in Heidelberg, invites international students holding a Master’s degree in (molecular) biology, (bio-)chemistry, (bio-)physics, computational biology, computer science, epidemiology / public health
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Senior Researcher in Ecosystem based marine management, nature restoration, and anthropogenic imp...
-index and ORCID (see http://orcid.org/ ) Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Applications received after the deadline will not be considered. All interested
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. As part of the DFG-funded
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems