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analyze and interpret multi-omic data to identify spatial patterns, cellular neighborhoods, and gene programs associated with drug resistance. Develop predictive models to infer tumor evolution and
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. The Ravnskjaer lab is headed by Assoc. Prof. Kim Ravnskjaer and focuses on cellular crosstalk in the regulation of liver function in health and disease. For this we apply single cell- and spatially resolved
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spatial network metrics. Strong quantitative skills, with experience in clustering analysis, data visualization, and statistical modelling. A research background in health-related topics. Demonstrated
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is the construction of tail dependence models that are flexible, parsimonious, and computationally tractable, and scale well as the dimension grows. Recently, Kiriliouk, Lee and Segers (2024, X-Vine
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related to staff position within a Research Infrastructure? No Offer Description POSTDOC IN DIGITAL PATHOLOGY Therapy-response prediction using spatial biology THE GROUP: The candidate will be part of
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the social and environmental implications of proximity models, combining spatial, mobility and socioeconomic data to develop indicators and tools for the toolkit. The candidate will also assume coordination
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will also develop skills in mathematical modelling and spatial analysis via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics
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Education and research background PhD in Economics, environmental economics and/or applied microeconometrics. Previous work in fisheries economics or related domains is desirable, but not mandatory Technical
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-seq, ATAC-seq, spatial transcriptomics, …) into modeling and develop efficient data/training pipelines Drive application cases with Helmholtz Munich, MDC Berlin, and NVIDIA—for example, disease modeling
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strategic programme. Through multiomic and spatial biology exploration of temporally distinct samples from clinical trials and advanced biological models, an international consortium of leading colorectal