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Informatics, or related fields. Strong programming skills in Python, R, or JavaScript for spatial analysis, interface development, or web applications. Experience in plugin or dashboard development (e.g
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-resolution microscopy with genome editing and advanced image analysis, we systematically assess how these methods can reveal disease-associated cellular phenotypes at unprecedented spatial resolution. Working
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of Geography and Spatial Planning (https://dgeo.uni.lu ), joining the Economic Geography team of Prof. Christian Schulz. The position contributes to the INTERREG-NWE funded AccessHubs project, which examines
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interpretable framework for tensor analysis. Specifically, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for
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or fragments). Practical experience of complex tissue analysis using multistaining techniques and image analysis. Practical experience of analysis of spatial proteomics and/or transcriptomics data. Experience
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experience in the analysis in at least one of the following domains: single cell genomics, WGS, WES, ChIP-seq, ATAC-seq, RNA-seq, spatial transcriptomics/proteomics, machine learning/deep learning models
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methylome sequencing, custom NGS panels, liquid biopsy, and spatial transcriptomics. The primary focus of this position is to help optimize and complete research tasks related to the computational analysis
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Basic and Applied Spatial Analysis Lab (BASAL). The BASAL is located within the Department of Natural Resources and the Environment at the University of New Hampshire. This researcher will work directly
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will be working in an experimental lab, performing data collection, analysis, and modeling of behavioral and electrophysiological data. Applications are invited to apply for a statistical data analysis
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, the recruited researcher will contribute to the development of a novel time-resolved fluorescence lifetime measurement approach, in close connection with methods based on single-molecule brightness analysis