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understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to
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degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system is required. The candidate must have interest and solid background in software systems, machine learning
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be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience
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important for renewable energy production and production variability will be an advantage. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and
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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
knowledge of artificial intelligence and knowledge of natural language processing. Proficiency in statistical analysis, such as econometrics and machine learning for survey data analysis. Experience with data
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-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System. J Med Chem. 2020). The lessons learned from the validation shall also be used to develop improved methods. About the LEAD
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project/work tasks: The SnowAI project aims to use to produce new high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD
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); mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. More about the position The position is