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Job Description Do you want to figure out why Bayesian deep learning doesn’t work? And afterwards fix it? At DTU Compute we are working towards building highly scalable Bayesian approximations
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for screening purposes and cell-based therapies. We will develop methods for modelling missing not at random (MNAR) observations and quantifying uncertainty using Bayesian methods and deep learning architectures
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sciences Strong background in deep learning, with experience in probabilistic models (e.g., Variational Autoencoders, Bayesian approaches) Proficient Python programming for machine learning and scientific
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