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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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data from existing cohorts and national registries, applying novel machine learning methods. The specific work tasks will include data management of large studies, scientific work related to the topics
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 9 hours ago
software development experience. PREFERRED: Experience with rotational spectroscopy, radio astronomy, radiative transfer calculations, and/or machine learning. These qualifications can be demonstrated
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the robot's physical embodiment suffer from poor generalization, weak explainability, and limited transferability; (ii) sample-inefficient learning requires large volumes of annotated, domain-specific data; and
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geoscientific applications. Current research includes large-scale crop mapping, wetland monitoring, and the integration of machine learning with remote sensing and geophysical data for groundwater mapping. Your
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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scientific software Prior experience with machine learning force fields is considered an advantage Experience handling large-scale datasets and FAIR data practices Please click here for the position’s
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enthusiastic scientist with the following competencies and experience: Essential experience and skills: You have a PhD in Machine Learning, Artificial Intelligence, Bioinformatics, Biostatistics, Epidemiology
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Computer Science, Electrical Engineering, Computer Engineering, or a related field. Preferred Qualifications Strong publication record in top-tier AI conferences or journals.. Strong written and oral