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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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, 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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machine learning models. Working with extremely large, multi-modal datasets. Prior experience in analysis of clinical health records, and time series data are highly preferred. Qualifications Requirements
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changing-look AGN/tidal disruption event/supernova host galaxy studies. Applicants with an interest in joint survey analysis methods, machine learning applications to survey data, and large-scale survey
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accelerate the transfer of new ideas from the lab to real-life applications, improving lives. The Horvath Lab at the Institute of AI for Health (AIH) aims to build large deep learning models for digital
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. Create predictive algorithms for the occurrence of cyanobacteria blooms; 3. Support field activities, process large volumes of data, and contribute to scientific publications. Requirements: • PhD in areas
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Universe (KMI)-PD [#31232, KMI-2025-2] Position Title: Position Type: Postdoctoral Position Location: Nagoya, Aichi 464-8602, Japan [map ] Subject Area: AI/Machine Learning / Astronomy Appl Deadline: 2025
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targets to treat anhedonia. Proposals that challenge prevailing assumptions, employ cutting-edge technologies, or integrate machine learning with neurobiological data are especially welcomed. Projects
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on the true, astrophysical candidates is a computational needle in a haystack. To tackle these “big data” challenges, astronomers have begun to employ machine learning techniques. The application of machine
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to Philip.torr@eng.ox.ac.uk For more information about working