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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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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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or spatial transcriptomics, or digital pathology) Strong programming (Python / R) and analytical skills, with proficiency in bioinformatics tools, statistics and machine learning. Experience with SQL
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or spatial transcriptomics. Strong programming (Python / R) and analytical skills, with proficiency in bioinformatics tools, statistics and machine learning. A creative and problem-solving mindset, capable
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. You will acquire the necessary skills for developing automated detection algorithms for spatio-temporally changing patterns and applying machine learning techniques for creating forecasts
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or application of machine learning/optimization methods Have good English communication skills An exceptional candidate may optionally have one or more of the following experiences: Experience in analyzing spatial