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The Einstein Telescope is a next-generation research infrastructure currently in development, featuring a large-scale computing center whose energy demands present a unique opportunity: to develop climate-neutral operations through the integration of renewable energy sources and hybrid storage...
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scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing predictive performance, generalisation
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involved in all phases of this process. You will Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML
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(zigzag and armchair) Local electronic structures (LDOS) The student will gain hands-on experience in ultra-high vacuum (UHV) operation, LT-STM/STS measurements, and the analysis of atomic-resolution
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FDSOI devices for neuromorphic computing applications Develop and optimize semiconductor fabrication processes in a state-of-the-art cleanroom environment Perform electrical characterization and analyze
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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are an advantage Please feel free to apply even if you do not yet meet all the required skills and qualifications. We may be able to provide training for these during the onboarding process. Our Benefits for You We
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companies. The project has partners from eight different EU countries. All 15 Ph.D. projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications in