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Field
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intelligent systems, all with a strong interactive component. The INtelligent Data Engineering Lab (INDElab) investigates intelligent systems that support people in their work with data and information from
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working on XAI and metadata creation, including both image and text analysis. You will organise benchmarks that assess AI technologies, particularly in the domain of newspapers, both current and historic
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advanced data on nature and biodiversity (derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision
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readouts such as Perturb-seq. Experience or familiarity with advanced genome editing methods such as prime editing, or base editing is highly desirable. Experience with bioinformatics data analysis using
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the analysis of primary material. We will aim for smooth integration of the experimental workflows and data analysis to address clinically relevant biological question in cancer immunology. We aim
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, genes, or metabolites significantly associated with plant phenotypes. These can in turn be experimentally tested by MiCRop partners. You will be part of the Biosystems Data Analysis (BDA ) group
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international and interdisciplinary project with research partners and stakeholders from five European countries. This position will focus on a spatial analysis of unsealing activities at a European scale and a
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developing AI driven ultrasound solutions by collaborating with the Diagnostic Image Analysis Group (DIAG). The Department of Medical Imaging is one of the leading centers in the world as also demonstrated by
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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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(derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision-making for solar and wind energy