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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
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its detailed analysis through Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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Convincing creativity and open mindedness Basic knowledge of the German language or the willingness to learn it for the purpose of knowledge transfer is welcome We offer: Freedom, independence Equipped working
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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling
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to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease
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to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so. The salary is paid according to the German TV-L system (the salary agreement for public service