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large-scale spiking neural networks. In close collaboration with our Mod4Comp partners (DFG Forschergruppe FOR 5880), you will develop models of performance and energy to guide the co-design of software
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Eberswalde University for Sustainable Development | Eberswalde, Brandenburg | Germany | about 7 hours ago
13 Mar 2026 Job Information Organisation/Company Eberswalde University for Sustainable Development Research Field Environmental science » Natural resources management Sociology » Societal behaviour
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en/judocs
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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Your Job: Determination of the lipid composition in human endothelial cells with and without oxidative stress Development of model membranes to mimic the endothelial membrane composition Analyzing
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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spectrum from basic and applied research to pre-industrial development and is carried out in cooperation with national and international partners from universities, academies and industry. The institute is
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits, such as grain yield, adaptation
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processes and infrastructures Development of control concepts for highly dynamic and load-flexible plants Coupling of technical, economic and ecological perspectives for optimised process design Experimental