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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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or http://github.com/modsim. Quantifying the activity of enzymes operating within the large-scale biochemical network is a fundamental challenge in Systems Bio(tech)nology. Here, the unknown parameters must
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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possible date, preferably by 1st April 2026. This is a full position (100%) limited to 3 years. This PhD position is available within the EU-funded Marie Skłodowska Curie Doctoral Network on Low Data Machine
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of the Biomaterials and Tissues of the Future. https://cordis.europa.eu/project/id/101226431 This network has 8 host institutions hiring doctoral candidates: Uppsala University, Universitat Politecnica de Catalunya
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analysis. Nat Biotechnol 41, 604–606 (2023). https://doi.org/10.1038/s41587-023-01733-8 We Offer Excellent framework conditions: state-of-the-art equipment and opportunities for international networking
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) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: https://atmosphere.ei.tum.de/ ) and in-situ sensor networks in ICOS Cities project (https://www.icos-cp.eu
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Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering principles and machine