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coefficient, which leads to optical aberrations and image degradation at elevated temperatures. In this AiF/ZIM project, funded within the framework of BMWK 2+2, the aim is to develop Ge crystals with
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) analysis • Research, development and implementation of deep-learning approaches • Network architecture search • Real-time image analysis • Establishing multi modal (video, thermography, acoustic, RFID
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expertise, we are creating functional genetic maps using conditional CRISPR/Cas9-based single and higher-order knockout perturbations combined with single-cell expression profiling and imaging. We expect
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analysis of omics and/or imaging data Interest in working with and for the digitalization of the ELM community. Self-driven and hands-on personality. Organization and prioritization skills. Very good
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internationally visible research environment with access to cutting-edge technologies in immunology, (spatial) multi-omics, advanced imaging and computational biology. Our requirements Applicants should hold a PhD
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-time (100 %) Published: 11.03.2026 Limitation:Temporary (2 years) Contract:TV-L Your tasks Phenotype disease courses in mouse models using immunological, molecular, and imaging-based readouts. Perform
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-throughput screening experiments and add new content based on literature Support the group in analyzing multi-omics data, such as RNASeq and images Analyze and present the results Collaborate with internal and
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal
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for research and software development tasks Define the overall architecture of the VIOLET research prototype, focusing on its role as a methodological demonstrator and ensuring interoperability with Medical
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quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework for tissue self