25 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral research jobs in Norway
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- University of Oslo
- Norwegian University of Life Sciences (NMBU)
- Peace Research Institute, Oslo (PRIO)
- UiT The Arctic University of Norway
- University of Bergen
- CMI - Chr. Michelsen Institute
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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developing an innovative microfluidic platform for human iPS cell-based neurodegenerative disease modeling. The project focuses on differentiating iPS cells to neurons, glia and other cell types involved in
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-based neurodegenerative disease modeling Apply for this job See advertisement About the position A three-year postdoctoral position is available at the University of Oslo under a project devoted to
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Ecosystem Mapping and Modelling Apply for this job See advertisement About the position Applicants are invited for a 4-year position as a postdoctoral researcher in Ecosystem Mapping and Modeling to be based
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22nd October 2025 Languages English English English Join NMBU’s PheNo project and advance AI-driven modelling in plant phenotyping. Postdoctoral fellow in Computational Plant Genetics and Digital
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are invited for a 3-year postdoctoral position financed by an Eranet program to investigate the impact of childhood adversities on adulthood psychopathology in a rodent model using in vivo electrophysiology
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climate change are far-reaching, particularly when it comes to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key
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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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work upon. Suggested reading to explore this line of research further: Kitto, K., Hicks, B., & Buckingham Shum, S. (2023). Using causal models to bridge the divide between big data and educational theory
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more