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resilience-centered approach, REUNATECH supports the European Green Deal, Sendai Frame-work, and UN Sustainable Development Goals. DCs will benefit from an immersive training structure comprising cross
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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perception experiments for prosodic analysis. For the advertised PhD researcher position, this work involves conducting prosodic production and perception experiments on reprise questions and other non
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system analysis or comparable Initial experience in optimization or statistics is an advantage Initial experience of an object-oriented programming language (e.g. Python, Matlab) and MS Office Analytical
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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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of techniques for the analysis of topological data. Targeted activities in the field of public relations are also planned. The activities will mainly be based at the Institute of Scientific Computing
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Menéndez Benito). The project aims to contribute to our understanding of how linguistic devices update the Common Ground by carrying out a systematic description and analysis of the evidential uses of verbal
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
biochemistry and molecular biology equipment. Additionally, there is a wide range of world-class facilities available for a plethora of analysis methods. The MPI offers programs for balancing work and family
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With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and resilient
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Simulations (LES). The analysis will be performed together with teams at the Helmholtz-Zentrum Hereon that focus on ocean turbulence and machine learning as a part of the TRR181 Collaborative Research Centre