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sub-sampling experience Experiences with paleogeographic modelling and the GPlates reconstruction freeware Scientific programming (e.g., Python) All candidates and projects will have to undergo a check
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cross-regional logistics network scenarios, data collection and development of decision support models for optimal maritime infrastructure for collection of the captured CO2 from the emitters and
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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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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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Technology is excitedto announce a vacant position of Postdoctoral Research Fellow in the area of sea ice model parameter optimization with Earth Observation data at UiT The Arctic University of Norway
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. Responsibilities will include data cleaning and management, performing quality checks, conducting statistical analyses applying causal inference methodologies, and contributing to the writing of high-impact
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universe. Its nominal sensitivity is close to the predicted signal range for a broad range of currently popular models, suggesting that a first cosmic CO detection could be imminent. COMAP is led by Caltech
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of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years, 10% of which is
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and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control
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. The models can build on recent research results in foundational neural network models. The work will be done in collaboration with Kongsberg Satellite Services in Tromsø. The position is located in Oslo, but