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Association. At the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI), we investigate the fundamental biological processes that drive aging. Our research combines molecular, cellular, and systems-level
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sampling strategies in Python and C++ Apply your framework to analyse real biological datasets to demonstrate robustness, interpretability, and practical impact Contribute to open-source software tools
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English, both spoken and written. German language skills are not necessary but a plus High motivation and work ethics No prior biological experience is required, but curiosity about biological questions
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motivation and work ethics No prior biological experience is required, but curiosity about biological questions, collaborating closely with experimentalists, and working with real-world data You share our
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optimise the developed methods on real biological datasets; work closely with experimental partners for interpretation and validation of results Contribute to the integration of the developed methods
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are not necessary but a plus High motivation and work ethics No prior biological experience is required, but curiosity about biological questions, collaborating closely with experimentalists, and working
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(guilt-by-association), and benchmark them against existing bulk co-expression resources Compare and optimise the developed methods on real biological datasets; work closely with experimental partners
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environment Very good English, both spoken and written. German language skills are not necessary but a plus High motivation and work ethics No prior biological experience is required, but curiosity about
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techniques more interpretable and biologically meaningful in their application to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly
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prior studies in the field. Thrust B: A second central thrust of this project focuses on making contemporary ML-based techniques more interpretable and biologically meaningful in their application