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scope of different subjects such as electrical engineering/electronics, microelectronics, microsystems technology, information technology, computer science, physics, chemistry, optics and manufacturing
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at international conferences and participate in summer schools and workshops A vibrant scientific network and mentoring program to support your career development The PhD degree awarded will be Dr. rer. nat. from
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programme culminating in either a PhD or a German Dr rer nat degree. Biomedicine The biomedicine section is involved in the study of physiological and pathophysiological processes. Research efforts focus
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techniques Physics » Applied physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 30 Sep 2025 - 23:59 (Europe/Berlin) Type of Contract Temporary
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 2 months ago
a powerful bridge between biology and engineering. The PhD offers training in computational neuroscience, neural circuit modeling, and AI/robotics, as well as strong interdisciplinary exposure through
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their system-level integration Develop design architecture and break down requirements into functional blocks Create and execute test benches for RTL and timing simulations Create design documentation in
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Degree PhD Course location Potsdam In cooperation with The innovative PhD and postdoctoral programme is offered in conjunction with the Faculty of Digital Engineering, a faculty jointly founded by
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 3 months ago
of computational load for such a development. In the frame of a third party funded research project, we are looking for a PhD Student to work on and develop breeding strategies to mine Winter-wheat accessions stored
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understanding of how genomic architectures drive soil carbon sequestration and will highlight microbial biodiversity suited to specific soils and climates, paving the way for more sustainable soil management
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architectures [5] and Neural ODEs [2], creating a cohesive end-to-end hydrological model. Transformers will be utilized to pre-process and analyse the raw input data, capturing essential spatial and temporal