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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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the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with
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has a strong background in control engineering, with documented expertise in optimal control, adaptive control and online optimization, stochastic systems, Bayesian inference, and state estimation and
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-year extension. The project is fully funded by the Independent Research Fund Denmark (DFF). The main objective of this project is to develop physics-constrained, data-driven turbulence models
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theory, physics, mathematics, computer science, and statistics. This Postdoc position falls under Research Thrust RT4 on Reliability and Trustworthiness. The objective is to explore and address research
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to advance local edamame production to meet the growing demand for fresh, nutritious and tasty plant-based food. To do that, the project’s objectives are: to identify soybean accessions with high adaptability
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to advance local edamame production to meet the growing demand for fresh, nutritious and tasty plant-based food. To do that, the project’s objectives are: to identify soybean accessions with high adaptability
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you to work with cutting-edge JWST observations of some of the most favorable targets for detecting and characterizing atmospheres around terrestrial and sub-Neptune planets. You are encouraged