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exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and
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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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the Institute of Bio- and Geosciences (IBG-4: Bioinformatics, headed by Prof. Dr. Björn Usadel) at Forschungszentrum Jülich. The position is embedded in subproject A12 of the DFG-funded Collaborative Research
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To expand our team “Process and Systems Assessment”, we are looking for several Postdocs or Senior Scientists with varying areas of expertise. Our research combines process modeling with techno
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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
Interfaces for Chemical Hydrogen Storage (IHE-1) investigates elementary reaction and degradation processes at catalytically active interfaces, from the atomic to the mesoscale. The team “Dynamic non
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entire FTS process in Aspen Plus, including reactions, separation and purification. Your model will then be coupled with an existing model of a 40-kW SOEC and reformer demonstrator unit. In a next step you
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segregation, interface-related energy losses, and insufficient process reproducibility. Addressing these challenges requires a workflow that connects rapid materials and process exploration with rigorous device
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passionate about AI research and eager to make a real-world impact, we want to hear from you! Your Job Work on a wide range of computer vision and machine learning methods and applications focusing