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. The position combines Empa UESL’s expertise in developing and accessing energy system models with the methodological expertise of the IMOS Laboratory in machine learning and foundation models. Postdoctoral
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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, and machine learning; and the development of ecological indicators for environmental monitoring in the Campos and Santos Basins, Brazil. Mandatory requirements Applications from people with training in
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 23 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies