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and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
, seeks a Post-Doctoral Associate or a Research Associate to join a lab focused on applied machine learning. The successful applicant will participate in research involving human computation, knowledge
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before starting—in computer science, electrical or computer engineering, information science, or a closely related discipline. Less than 5 years post receiving the Doctoral degree. Meet the mandatory
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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Required License/Registration/Certification NA Physical Requirements Present in a classroom; regular use of computer Shift Per course schedule Job Summary The School of Information Science (SIS) in
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across learning sciences, computer science, machine learning, HCI and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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studies in the area of machine learning for wireless communications. Develop and implement machine learning techniques for communication systems, with a strong emphasis on producing high-quality research
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Difallah in the Division of Science, New York University Abu Dhabi, seeks a Post-Doctoral Associate or a Associate Research Scientist to join a lab focused on applied machine learning. The successful
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the