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menopausal women.” The position is part of the EU-funded Marie Skłodowska-Curie Actions Doctoral Network MenoBrain “Brain Health in Menopausal Women” with full-time employment for a duration of 3 years
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incorporate methods that integrate: - Mendelian randomization and genetic instruments - Bayesian hierarchical models and Gaussian graphical models - Multi-layer data integration across tissues and omics
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mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design
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19 Sep 2026 Job Information Organisation/Company MAX PLANCK Institute for Human Cognitive and Brain Sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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Experiments (DoE) and Bayesian optimization, manage research data using the NOMAD research data infrastructure, and apply data-driven optimization strategies. Analyze and interpret experimental data
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Neuroplasticity in Development and Learning explores how the human brain develops from the prenatal period through infancy, childhood, and into adulthood, and how experience shapes brain organization and function
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 2 months ago
on the glymphatic system, a brain-wide fluid transport network that facilitates the clearance of metabolic waste and neurotoxic proteins from the central nervous system. Growing evidence suggests that impaired
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science, computational neuroscience and causal AI. You will collaborate with internationally recognized researchers and contribute to developing novel methods for understanding brain dynamics. The current
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of this PhD project is to decipher the regulatory mechanisms underlying RNA dysregulation in response to environmental and viral stressors. Using innovative brain organoid models, you will apply computational
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project-specific requirements. Students can deepen their knowledge about selected topics (e.g. Bayesian Statistics, HMMs, AI, advanced programming in Python) in small classes of max. 10 participants