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with data-based models and numerical dynamo simulations. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events
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ecosystem functioning. The postdoctoral project will focus on analyzing and modeling tree architecture in relation to forest vitality and stress predisposition. The work will combine 3D structural data (from
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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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strategies for conventional HVAC systems that condition entire indoor spaces using existing thermal comfort models, which could improve the performance of existing buildings and HVAC systems. The work will
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target trials, group-based trajectory modelling, mediation analyses, and Bayesian modelling approaches to investigate adherence to cancer treatment and recurrence. The research fellow will join a vibrant
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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disease, with a strong focus on fibrosis and inflammation. Over the years, we have developed an advanced translational toolkit, including human precision-cut tissue slices, a unique organotypic model
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through the Internet of Things create new opportunities to incorporate real-time insights into decision-making, combining tractable modelling with provably efficient solution methods. As a postdoctoral
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in vivo models to investigate drug responses in relation to immune-cell mediated killing of multiple myeloma cancer cells. Your job responsibilities As Postdoc in Cancer immunology/multiple myeloma
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models using sophisticate genetic tools, in vivo time-lapse imaging and multi-omics methods to decipher the underpinning mechanisms of regeneration. Our findings provide new targetable mechanisms