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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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. It is a prerequisite that you complete the project during the employment period. Qualification requirements You must have a PhD with a specialisation relevant for the project. The PhD thesis must have
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will contribute to developing knowledge-driven decision-making models. The postdoctoral research fellow will actively participate during the supervision process of PhD-students as main or co-supervisor
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the supervision process of PhD-students as main or co-supervisor. The postdoctoral research fellow will be part of an interdisciplinary team to design new outcome measures for pain and behavioral and psychological
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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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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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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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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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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