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Field
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with environmental/scientific datasets (cleaning, processing, analysis, synthesis). Strong programming skills, especially Python (or comparable scientific programming). Experience with LLM-assisted
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-epithelial interactions. The role employs a multi-modal research approach spanning genetically engineered mouse models, histopathology, mouse and human organoids, CRISPR-Cas9 gene editing, single-cell
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
. The host research group leads a number of projects on the development of theoretical and applied methods in statistical modelling, medical imaging data analysis, cancer omics, precision medicine and
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and present experimental data. This includes applying computer analysis and simulation programs to interpret experimental data and characterize battery electrode materials and interfaces. Adapt and
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
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and methodologies, including EEG, NIRS, MRI and diffusion imaging techniques. Familiarity with human-subject research methodologies, experimental design, and statistical analysis. Required Skills
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. Empa is a research institution of the ETH Domain. The group Multi-omics for Healthcare materials at Empa St. Gallen generates and integrates multi-modal biomedical datasets with the aim to inform
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therapeutic modality due to cargo capacity, low immunogenicity, and tissue-specific targeting. The United States Food and Drug Administration (FDA) requires that manufacturers demonstrate that every drug lot is
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bioinformatic analysis of the resulting datasets. You will work to integrate proteomic data with orthogonal single-cell modalities including transcriptomics and imaging, and collaborate closely with clinical and
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sciences. The PostDoc research will be part of a multi-center research project on applying and combining multi-modal 2D and 3D imaging methods for understanding metastasis and tumor deposit formation in