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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
Biotechnology ), we develop agentic AI and “virtual cell” models in the context of the Human Cell Atlas and the European Lab for Learning & Intelligent Systems , powered by large-scale single-cell, spatial, and
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research for an NIH-NSF funded project on human health, movement, and infectious diseases. Successful applicants will have experience in: Either spatial analysis using GIS or disease modeling in R and/or
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to help define a new frontier at the interface of spatial biology and therapeutics. The scholar will lead spatial-biology driven projects to identify novel spatial biomarkers, therapeutic targets, and
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, including vision, LiDAR, inertial measurements, and radio signals, to maintain coherent spatial awareness and act reliably under uncertainty. A particular focus will be placed on learning and decision-making
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Duties: Attend introductory training sessions organized by the project PI and Co-PI's. Integrate complex large datasets from open sources and SAS Viya, including spatial and temporal environmental
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generating and working with large datasets (e.g., tissue RNA sequencing, single cell RNAseq, spatial proteomics or transcriptomics) Technical experience with primary cell culture and cell culture
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. Preferred qualifications ● Fluency in fisheries and/or bioeconomic modeling, with experience in spatial fisheries ecology or management strongly preferred; ● Advanced understanding of the biology and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
RNAseq and spatial profiling. Several projects are available. One project seeks to define microbial mechanisms driving inflammation-associated intestinal fibrosis (see PMC12488000). Another will define
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models, flow cytometry, confocal microscopy and unbiased approaches such as single cells transcriptomics, spatial transcriptomics and epigenetics to characterize molecular and cellular mechanisms. Using
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-seq, RNA-seq, ATAC-seq and spatial transcriptome data. We are also interested in developing modern statistical approach for integration of multi-omics datasets and causal inference to understanding