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issues will get particular attention. First, identify the most appropriate environmental, economic and societal impact categories to include in the assessment. Second, develop the three models
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application of the new methods will be co-designed with the candidate to best match their research interests. As a PhD-candidate at the Department of Earth Science, University of Bergen, you will also be
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big data and advanced methods for modeling exposures, we will establish real-world patterns of hormonal contraceptive use and mental disorders, and identify potential moderating factors such as
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work on adapting or developing marine foundation models. Self-supervised learning and active learning are also possible research topics. You can also focus on challenges related to modelling physics
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in the μ-opioid receptor. The PhD candidate will: • generate high-resolution models of wild-type and R181C mutant μ-opioid receptor based on existing crystallographic data and perform molecular
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of department. Various research topics can be explored, depending on the applicant’s interests. Possible themes include: 1) the changing Meridional Overturning Circulation, from models and in situ data
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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learning methods for generating complex structures for generation of virus capsids and therapeutic proteins for gene therapy. The project will involve both physics-based forward modeling of protein
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candidate to develop Machine Learning models and frameworks for time series analysis, aimed at understanding how the human brain encodes information. This cross-disciplinary project is a high-level
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of hypothermia with important medical implications. To study this, the Ph.D. candidate will use mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems