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Field
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. The successful applicant will integrate multi-modal live imaging and omics data using AI-based pipelines to identify and refine early disease phenotypes, laying the groundwork for therapeutic intervention
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modalities. Therefore, the ideal candidate will be expected to conduct homologous overexpression, gene silencing, sequence analysis and contained phenotyping. Education A PhD in Molecular Biology, Genetics
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artificial intelligence (AI). The successful candidate will play a key role in developing a multi-modal generative AI framework aimed at exploring how coastal wetland ecosystems across the Southeastern
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background in data sciences we ask: Insights in the most suitable data science techniques (e.g., machine learning, cluster analysis) to answer specific research questions based on available data as a basis for
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on the analysis of different characteristics of the skin and body fluids, such as sweat and blood. Many of these methods are challenged with quality (accuracy/precision of measurement), power consumption, usability
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lead sophisticated multimodal bioinformatics integration and analysis, collaborating daily with a diverse team of computational scientists and clinicians to translate complex data into actionable cancer
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to creativity in AVT in different translation modalities, define whether user attention and preference is linked to creativity, and gather data on how errors affect user attention. You will use a mixed method
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in relevant research fields Desirable criteria Multi-modal image analysis expertise Real-time detection and segmentation methods for clinical applications Surgical video analysis, e.g. workflow
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collaboration across the consortium. Analyse stakeholder input using appropriate frameworks (e.g. thematic analysis, policy benchmarking) to inform consensus-based recommendations. Ethics & Project Management
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, Science, 2022), especially in the context of drug-host microbiome interactions, and the development of dedicated tools for the novel data modality generated by Record-seq. Job description We are looking