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Profile: University degree (M.Sc., diploma or equivalent) in materials science, engineering sciences, or physics Experience in at least one of the methods of X-ray imaging, transmission electron microscopy
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strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center
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to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component
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professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities - more information about the PhD program at the HZDR can be found
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Equity Fields of Action Networks for Equity Kontakt Team Equity News and publications Back Press Releases attempto online Newsletter Uni Tübingen aktuell University of Tübingen magazine Attempto
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structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de
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your research at conferences, workshops, and through scientific publications. Your profile: ▪ You hold an MSc degree in physics, engineering, or computer science. ▪ You are very experienced in Python
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Description The Institute for Software and Systems Engineering (ISSE) of the University of Technologies Clausthal is hiring a academic researcher in the field of stakeholder networking & living lab
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 14 hours ago
Dresden University of Technology (TUD) Course location Dresden In cooperation with Dresden University of Technology (TUD) Teaching language English Languages The programme is conducted in English. Full-time
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engineering with TensorFlow or similar frameworks Ability to develop Spiking Neural Networks from scratch, including training and quantization Optimize and benchmark applications and models for neuromorphic