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analyses of single-cell and spatial omics to advance precision medicine. Dr Chen’s research team develops AI algorithms for spatial and single-cell omics, integrates publicly available datasets into a
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models for bridging knowledge gaps, data scarcity and uncertainty gaps, and governance gaps related to monitoring the environment on which humans depend. A part of this is **spatial statistics of sensor
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Your position You will develop generative models on single-cell and spatial genomics data, from sequencing and imaging, and apply them to human developmental and disease biology. Possible research
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models for bridging knowledge gaps, data scarcity and uncertainty gaps, and governance gaps related to monitoring the environment on which humans depend. A part of this is **spatial statistics of sensor
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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
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environmental data products. Assist with development of spatially explicit Manning roughness coefficient surfaces and related crosswalk tables for hydrodynamic modeling. Quality assurance, quality control, and
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and brings creative thinking to complex spatial and environmental challenges. Responsibilities* GIS Mapping & Spatial Analysis: Utilize GIS software (ArcGIS Pro) to compile, digitize, and analyze
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vivo cancer models, pharmacologic inhibitors, immune profiling, and spatial omics to investigate how the metastatic microenvironment regulates tumor progression and immune suppression. Organized, honest
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advances in acoustic individual identification (AIID) with state-of-the-art acoustic spatial capture-recapture (SCR) modelling. Together, these will move acoustic monitoring from species detection to within
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modelling. References/further reading Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868-876 (2023). Danenberg, E. et al. Breast tumor