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Field
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such as comparing spatial locations across time, highlighting changes in various dataset components, and integrating ancillary information layers within a fully three-dimensional (3D-in-3D) workspace
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Two fully-funded postdoctoral or PhD student positions in experimental mesoscale bioinspired materials, DNA nanoscience, and/or soft matter physics The university: Johannes Gutenberg University
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technologies (e.g., spatial transcriptomics, CODEX, Akoya PhenoCycler). Proficiency in single-cell RNA sequencing, high-dimensional data analysis, bioinformatics tools, and programming languages (R, Python
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-analysis software; managing procurement and technical liaison with campus workshops; planning and analysing imaging experiments with collaborators; supervising and mentoring junior researchers; and
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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required Experience analyzing wearable device data including accelerometer and GPS data, as well as experience with spatial data analysis Demonstrated publication record in high quality peer-reviewed
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Job Description We invite applications from highly motivated and talented researchers for a 2-year postdoctoral position in advanced skin models, cellular immunology, and spatial transcriptomics
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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understanding of myocardial regeneration, neoangiogenesis, immunomodulation, and anti-fibrosis at the molecular level, with spatial resolution. To be successful in this role, you will hold a relevant PhD/Dphil