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networks and flow fields in porous materials Evaluation of large tomographic data sets as input for mechanistic and AI-based reactive transport models Presentation and publication of original scientific
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applications for a PhD-student (m/f/d; 65%, 3 years in first instance) to work on a large-scale €6m multi-site Wellcome-funded project. This position is suited for researchers who have finished or are about to
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digitalized society, a climate-friendly energy system, and a sustainable economy. We focus on the natural, life, and engineering sciences in the fields of information, energy, and bioeconomy. We combine
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instrumentation and high‑performance data acquisition and signal‑processing systems. We contribute to large-scale research projects such as Pierre Auger Observatory, Belle II, CMS, LHCb, FCC-ee, XENONnT, DELight
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. Hoffmann’s research group, an innovative project is being conducted on the processing and analysis of seismic data from a large-scale Distributed Acoustic Sensing (DAS) network. This network is installed
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well as professional and personal support. The scholarship holders are supported in their personal development with a large number of offers. This includes soft skill seminars and language courses as well as summer
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whether it may fit your interests, please read some recent papers by our lab before you apply. Additional Information CISPA and the University of Stuttgart have a large interest in increasing the number
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part of a large collaborative research center “Quantitative Synaptology” (SFB1286), and focuses on investigation of the regulatory role of the synaptic vesicle cluster. The synaptic vesicle cluster is a
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responses. Among these, Nucleotide-binding, Leucine-rich-Repeat proteins (NLRs) constitute a large family of intracellular receptors of pathogen-associated molecules, termed effectors. To restrict infection
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of mechanobiology in the pathogenesis of neurodegenerative diseases. Investigators in the consortium have expertise in mechanobiology, neurodegeneration, DNA damage, neuropathology, medical imaging and big data