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Your Job: Combine multimodal brain imaging with advanced image-processing, data science, and AI techniques to perform image alignment, segmentation, and classification to construct and validate
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the research group “AI for Image-Guided Diagnosis and Therapy” of Benedikt Wiestler at the TUM School of Medicine and Health. The project is about developing next-generation DL algorithms using attention
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Open Position: (Postdoctoral) Researcher (m/f/d) Model Building for SPM Images of Macro(bio)molecules Job Code: 03.25 Your project: Build and test a GPU‑accelerated program to detect and interpret
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erythematosus (SLE). This project will integrate biochemical, immunological, and imaging techniques, along with co-culture of patient-derived organoids and model organisms combined with various –omics approaches
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to emerging carbon dioxide removal techniques. To this end, distributed pelagic imaging techniques enable the sustained observation of aquatic life and its debris, comprehensively covering the earth’s water
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improved patient outcomes Integration of findings into translational research, collaborating closely with clinicians, imaging specialists, and bioinformaticians to optimize interventional oncology treatments
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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medical machine learning for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and build their early scientific career. About
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cancer Establish single-cell perturbation screening approaches to investigate cell fate decisions and disease mechanisms Integrate high-content imaging, single-cell transcriptomics, and functional assays
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culturing, integrating multiple automated subsystems with image-based machine learning models. Our objective is to enable robotic decision-making through machine learning, paving the way for a standardized