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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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project is part of our current activities on developing new antibiotics based on pleuromutilins. The goal of this project is to identify a hit compound specifically targeting multi-resistant Gram-negative
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-termed position for 24 months from 1st of May 2026 or as soon as possible thereafter. Job description You will be working with antibodies targeting a-synuclein aggregates for therapy against Parkinson’s
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. The postdoctoral project is part of our current activities on developing new antibiotics based on pleuromutilins. The goal of this project is to identify a hit compound specifically targeting multi-resistant Gram
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that they often target disadvantaged groups or affect groups differently. While such efforts potentially promote equality, including labour market and health equality, policies that target or affect
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approaches and experimental models, the work will investigate how targeted regulation, through diet, of gut microbial functions and microbial metabolites can influence host metabolism. These concepts will be
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Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we strive to support our scientific