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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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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