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ecosystem models. Experience using high-performance computing systems. Proficiency in running numerical ocean models. Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting
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and to identify new therapeutic targets and prognostic biomarkers. Novel data integration methods allow to identify signatures of retinal cell types in liquid biopsies without the need for a direct
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molecular/condensed matter physics) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a
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: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
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biology, biochemistry, nutritional sciences or another biological/medical field Expertise in chronobiology and circadian rhythms analysis Experience in general molecular and cell biology methods Experience
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human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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upcoming AI methods to analyze the climate simulations. The interdisciplinary character of the project also asks for strong skills in communicating with project partners in coordinating research tasks
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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to the Baltic Sea region. Experience in running numerical ocean models and analyzing ecosystem model output. Experience using high-performance computing systems. Familiarity with operating systems such as Linux