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Field
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partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
and fastest-growing fishery in the Southern Ocean, regulated by the CCAMLR, which aims to manage the fishery sustainably, relying on ecosystem-based approaches incorporating data on predator populations
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discussions and team meetings Taking over project responsibility Collaborating closely within an interdisciplinary research team sincere interest in analysis of large scale data - we can provide guidance Your
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-organization. For more information go to: https://www.bauschlab.org Your Qualification: High motivation, curiosity, and commitment to scientific excellence Master's degree (for PhD) or PhD (for PostDoc) in stem
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candidates which are explored in more depth. In particular you will work on the extension, development and analysis of new quantum algorithms for near-term and fault tolerant quantum computers for drug
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-studies have shown that full automation is possible in principle when formally verifying systems using reachability analysis. However, our pre-studies also showed that further research is needed
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energy system optimization and control Engineering, Applied Mathematics or a comparable quantitative discipline Very good software development and data analysis skills Inquisitive and passionate about
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are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random network coding
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advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US
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-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators. Furthermore, we aim