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, method-driven theory to application-driven research. Please find more information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your tasks in detail: Review existing literature, collect
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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Are doctoral positions paid? All doctoral positions are fully funded, including social benefits. Students also receive funding to attend conferences and other events related to their research, and have access to outstanding facilities. Do I need to know English? Yes, English is the institute’s...
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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for applications for PhD positions. The Leibniz Graduate School on Aging (LGSA) belongs to the Leibniz Association - a non-university research organization equivalent to the Max Planck Society and the Helmholtz
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding
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-source software, scientific publications, and a PhD thesis. Your tasks within framework in detail: Conduct a literature review on modern techniques for combining models with observational data, with a