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, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate
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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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be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
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, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate
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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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(e.g., Bayesian inference, deep learning), ideally connected to spatial omics, and experience with frameworks like PyTorch, Keras, Pyro, or TensorFlow Application process: Interested candidates should