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the organising principles of biological information processing, focusing on the underlying physics of computations and sensory environments. This exploration has led to developing models and advanced statistical
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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innovative research utilizing wet-lab techniques, 3D models, and extracellular vesicles to advance our understanding of drug resistance in melanoma. Your responsibilities: Conduct wet-lab research in melanoma
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more (for an overview of these technologies, see http://behaverse.org/ ). Your role in this team will be to develop computational models and data analysis code to process large, multimodal behavioral
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various
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a powerful model for uncovering muscle-specific protective processes. Yet, significant gaps in our knowledge have hampered advancement in this field including the lack of molecular markers and
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progression. This project addresses the challenge of studying early tumorigenesis in pancreatic cancer by developing advanced in vitro models based on human extracellular matrix (ECM), aiming to recreate
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the immunological dysregulation inherent in T1D. Project Objective The PhD candidate will primarily focus on the clinical
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stacking, both high performance and (very) high density can be achieved by this concept. The mission will be to explore, understand and develop the fundamental physics of device operation. This will require