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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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mechanisms. The postdoctoral fellow will take the lead on this endeavor, in collaboration with a PhD fellow focusing on brain function and health. PlastBrain is a collaboration between the Department
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for a position as associate professor in Norway, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of
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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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-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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associate professor in Norway, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting
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one Postdoctoral Research Fellowship at the University of Oslo. Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic pedagogical competency in the course
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engage with previous empirical literature on iconicity and iterated learning experiments. The candidate will help train the PhD candidate and train and supervise research assistants. The position is
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perspectives. FemArc is a central activity in ConGender, focused on work in progress, and recruits beyond ConGender. The teaching consists of a one-year programme at BA level and two PhD courses. The one-year
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for Knowledge-driven Machine Learning. We are looking for a motivated researcher, who has experience with both theoretical, methodological and applied research in change and anomaly detection in sequential data