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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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effector functions. Such understanding is essential for the development of new therapies against cancer and infectious diseases. Further information on our work can be found on our homepage and in our
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data analysis and quantitative evaluation of imaging or histological data Fluent in English and strong communication skills in an international team environment Benefits Opportunity to integrate into a
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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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information about the program can be found at Doctoral studies at the Faculty of Medicine . Background and description of tasks The PhD student will use state-of-the-art methods such as cryo-electron tomography
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disciplines and sectors. More information can be found at www.ukri.org and www.mrc-lmb.cam.ac.uk. Closing date: 07/09/2025 Final appointments will be subject to a pre-employment screening. We actively support
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), immunofluorescence and microscopy Prior experience in RNA biology, NGS and/or Metabolism is an asset Understanding of common bioinformatics approaches and experience with one of the main programming languages for data