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AM) Position Description: Apply Position Description Postdoctoral Associate in Multi-omics analysis Dr. Serpa’s Laboratory - Cyte Department of Population Medicine and Diagnostic Sciences College
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background in machine learning and data analysis Interest in single-cell omics, spatial data, and data integration Intellectual curiosity, independence, and motivation to tackle open-ended problems with real
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, or closely related discipline. - Expertise in data management, spatial analysis, GIS, and R/Stata programming methods. - Experience working in a team and under a deadline. - Strong written and interpersonal
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applications for fully-funded postdoctoral research associate positions. SITE is highly interdisciplinary and aims to develop novel enabling technology on hydrodynamic stability analysis that has applications in
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cell fate specification. The project will focus primarily on the analysis and comparison of single-cell RNA-seq datasets from different animal groups, including multi-omics and spatial transcriptomics
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, sediment transport/deposition, landscape change); You enjoy working with large datasets and applying statistical analysis and modelling approaches; You use scripting/programming in your research (e.g. Python
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or treatment of Alzheimer’s disease. Position Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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existing stable isotope facility. The Department of Earth Sciences at the University of Delaware houses a state-of-the-art stable isotope laboratory (https://sites.udel.edu/eis-lab/ ) equipped with advanced
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III will be responsible for specimen tracking, processing, organization and analysis. The Research Associate III will be expected to maintain detailed records of experiments and activities according
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machine learning (ML)) and emerging data types (electronic health records (EHR), biobanks and disease registries, and next-generation genomics including single-cell and spatial omics); communicates clearly