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with microstructural features and failure mechanisms Development of models to describe degradation mechanisms and predict component lifetime Presentation of research findings at project meetings
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investigating degradation mechanisms within the framework of green energy conversion and climate change. The open position aims to understand catalyst stability at the nanoscale during electrochemical processes
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Description For our location in Hamburg we are seeking: PhD Position in Laser Plasma Acceleration Remuneration Group 13 | Limited: 3 years | Starting date: earliest possible | ID: MDO004/2025
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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
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Tackle the challenge of computationally expensive meta-optimization procedures by developing and using dedicated tools and processors Contribute to our sparse auto-differentiation libraries to accelerate
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accelerators for science. Currently, the new FAIR (Facility for Antiproton and Ion Research) one of the world´s largest research projects, is being built in international cooperation. GSI and FAIR offer
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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developing and using dedicated tools and processors Contribute to our sparse auto-differentiation libraries to accelerate the training of state-space models Collaborate closely with our internal partners
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: Develop an event-driven RL algorithm that sparsely updates network state and parameters that will significantly improve energy to-solution efficiency compared to conventional digital accelerators when
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of Mg-LPSO alloys that have undergone degradation in a physiological environment using X-ray nanotomography with the highest achievable resolution Localization and focused ion beam preparation