591 computer-security "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" PhD positions in Germany
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 19 hours ago
cooperates closely with all faculties , the BTU Research Department, and the BTU Welcome Centre . Qualification Programme: In addition to your independent research, the GRS also offers you a comprehensive
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: https://www.uni-giessen.de/en/faculties/ggkgcsc/graduate-programmes/phdnet/phdnet Integrated internships An internship is not part of the programme. Teaching/work obligations or opportunities Members have
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within the faculty participate in the programme. The course content is very broad and the specific subject of the dissertation depends on the institute. For research subjects, please see our website: http
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Anticipated Start Date: 01.03.2026 Application End Date
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Italian Languages Participants can choose to write their doctoral dissertation in French, German or Italian. Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application
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Materials” with its about 100 members is a central structural element of the Cluster. It offers a training programme preparing the doctoral researchers not only for their research career and their work in the
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. All the lectures, courses and workshops offered are in English. Students write and defend their doctoral theses in English. Full-time / part-time full-time Programme duration 8 semesters Beginning
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9 Jan 2026 Job Information Organisation/Company Academic Europe Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key