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Field
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research and handling sensitive data is preferred. • Strong quantitative skills, including proficiency in regression modeling, environmental mixtures analysis, and spatial methods using R. • Familiarity with
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to support community-based organizations, funders, and other stakeholders working towards social, racial, economic, and environmental justice. ERI produces data-driven analysis and rigorous research to inform
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://pritykinlab.princeton.edu ) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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, but starting time is flexible. Focus of the project is the investigation of the link between the dynamics of synaptic structural plasticity and the probability of neurons to become active during spatial
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 months ago
interdisciplinary collaboration. Demonstrated programming skills, preferably in Python (e.g., PyTorch, NumPy, pandas, polars). Experience with spatial and/or temporal data analysis (geographic data, satellite imagery
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: Geographic Information Systems (GIS): Knowledge of GIS for spatial analysis, including tools such as ArcGIS or QGIS. Publication & Presentation Experience: Experience in publishing research in peer-reviewed
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monitoring and profiling of breast tissue and systemic responses; Use of mouse models to study early tumour initiation; Application of single cell and spatial transcriptomics, lineage tracing, and multiomics
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dosimetry. The simulation includes dose deposition and analysis under a phantom system and compares the simulated results with already developed new generation dosimeters used under treatment planning systems
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. The successful candidate will: 1) Lead the development of computational pipelines for the integration of large-scale single-cell omics datasets, including single-cell CITE-seq, scATAC-seq, and spatial