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Field
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Research Fellow in Machine learning Apply for this job See advertisement About the position Position as PhD Research Fellow in Machine learning connected to the Scientific Computing and Machine Learning
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The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently adopted in CLM-FATES at UiO. The aim is: to constrain
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software
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power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English English requirements for applicants from outside
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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Econometrics Virtual power plants Power systems and/or power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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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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subsidy for research costs. Information on sponsorship during the research stay Information on sponsorship for alumni abroad Postdocs Benefit from research sponsorship in Germany at the beginning of your
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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