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the entire population. The project utilises advanced statistical methods such as multilevel models (mixed models), fixed-effects models, cluster analysis, and sequence analysis. The selected researcher is
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is looking for a postdoctoral researcher, doctoral researcher or project researcher to develop machine learning methods for health data analytics. The fixed term position starts on mutual agreement
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, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health, policy, and technology design
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candidates from diverse academic backgrounds, including architecture, computational design, computer science, or related fields, who have a proven track record of applying advanced computational methods
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. Integrate environmental, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy
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compared with observations, offering a powerful way to test our theories. The combination of novel AI methods and broad statistical analyses will help us pinpoint the exact roles of solar flares and coronal
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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
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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cytometry, other immunological methods and mouse colony management is required. The applicant should have the ability to work productively both independently and as part of a team. The position is available
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, infrastructure regulation, trade) Interest in the geopolitics of cloud infrastructure or digital sovereignty Strong collaboration and communication skills Basic knowledge of quantitative methods (e.g. multiple