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randomization and genetic instruments
- Bayesian hierarchical models and Gaussian graphical models
- Multi-layer data integration across tissues and omics modalities
- Network-based regularization -
, biomedical systems, neuroscience, and safety and security. The Division of Systems and Control enjoys a wide network of strong international collaborators all around the world, for example at the
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analyses; computational or statistical modelling; Bayesian statistics; programming behavioural experiments; research on attention, perception, or eye movements; preregistration, FAIR data management
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on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic data. The aim is to enable meaningful analyses, such as
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but could become disruptive in the future. The team operates to high academic standards, publishes in peer-reviewed journals and conferences, and has built a broad European and international network